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Wilcoxon signed-rank test

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rank procedure; but increasing some of the values so as to break the ties, or breaking the ties in any way whatsoever, results in a sample that the test judges to be not significant. However, increasing all the observed values by the same amount cannot turn a significantly positive result into an insignificant one, nor an insignificant one into a significantly negative one. Furthermore, if the observations are distributed symmetrically, then the values of
14733: 14721: 1907: 8642: 6461:. The rank assigned to an observation depends on its absolute value and the tiebreaking rule. Observations with smaller absolute values are always given smaller ranks, just as in the standard rank-sum test. The tiebreaking rule is used to assign ranks to observations with the same absolute value. One advantage of tiebreaking rules is that they allow the use of standard tables for computing 1545: 8329: 122:
There are two variants of the signed-rank test. From a theoretical point of view, the one-sample test is more fundamental because the paired sample test is performed by converting the data to the situation of the one-sample test. However, most practical applications of the signed-rank test arise from
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of the differences between paired individuals cannot be assumed. Instead, it assumes a weaker hypothesis that the distribution of this difference is symmetric around a central value and it aims to test whether this center value differs significantly from zero. The Wilcoxon test is a more powerful
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breaks the ties at random. Under random tiebreaking, the null distribution is the same as when there are no ties, but the result of the test depends not only on the data but on additional random choices. Averaging the ranks over the possible random choices results in the average rank procedure. One
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Under the average rank procedure, the null distribution is different in the presence of ties. The average rank procedure also has some disadvantages that are similar to those of the reduced sample procedure for zeros. It is possible that a sample can be judged significantly positive by the average
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Wilcoxon's original paper did not address the question of observations (or, in the paired sample case, differences) that equal zero. However, in later surveys, he recommended removing zeros from the sample. Then the standard signed-rank test could be applied to the resulting data, as long as there
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From the viewpoint of statistical efficiency, there is no perfect rule for handling zeros. Conover found examples of null and alternative hypotheses that show that neither Wilcoxon's and Pratt's methods are uniformly better than the other. When comparing a discrete uniform distribution to a
5094:. Pratt argues that one would expect that decreasing the observations should certainly not make the data appear more positive. However, if the zero observation is decreased by an amount less than 2, or if all observations are decreased by an amount less than 1, then the signed ranks become: 2240: 5361:
A sample is significantly positive, not significant, or significantly negative, if and only if it is so when the zeros are assigned arbitrary non-zero signs, if and only if it is so when the zeros are replaced with non-zero values which are smaller in absolute value than any non-zero
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is reported, an equivalent way to compute the rank correlation is with the difference in proportion between the two rank sums, which is the Kerby (2014) simple difference formula. To continue with the current example, the sample size is 9, so the total rank sum is 45.
1902:{\displaystyle {\begin{aligned}T^{+}&={\frac {n(n+1)}{2}}-T^{-}={\frac {n(n+1)}{4}}+{\frac {T}{2}},\\T^{-}&={\frac {n(n+1)}{2}}-T^{+}={\frac {n(n+1)}{4}}-{\frac {T}{2}},\\T&=T^{+}-T^{-}=2T^{+}-{\frac {n(n+1)}{2}}={\frac {n(n+1)}{2}}-2T^{-}.\end{aligned}}} 8637:{\displaystyle {\begin{aligned}\mathbf {E} &=\mathbf {E} ={\frac {n(n+1)}{4}},\\\mathbf {E} &=0,\\\operatorname {Var} (T^{+})&=\operatorname {Var} (T^{-})={\frac {n(n+1)(2n+1)}{24}},\\\operatorname {Var} (T)&={\frac {n(n+1)(2n+1)}{6}}.\end{aligned}}} 8833: 4949:(in the paired sample case). This is particularly common for discrete data. When this happens, the test procedure defined above is usually undefined because there is no way to uniquely rank the data. (The sole exception is if there is a single observation 5722:(except when there are no ties). The rank assigned to an observation is the average of the possible ranks it would have if the ties were broken in all possible ways. Once the ranks are assigned, the test statistic is computed in the same way as usual. 4198:
The null hypothesis of exchangeability can arise from a matched pair experiment with a treatment group and a control group. Randomizing the treatment and control within each pair makes the observations exchangeable. For an exchangeable distribution,
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PROC UNIVARIATE includes the Wilcoxon-Signed Rank Test in the frame titles "Tests for Location" as "Signed Rank". Even though this procedure calculates an S-Statistic rather than a W-Statistic, the resulting p-value can still be used for this
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could also report the probability of rejection over all random choices. Random tiebreaking has the advantage that the probability that a sample is judged significantly positive does not decrease when some observations are increased.
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Because the paired data test arises from taking paired differences, its null and alternative hypotheses can be derived from those of the one-sample test. In each case, they become assertions about the behavior of the differences
5901: 357:. Assume for simplicity that the observations in the sample have distinct absolute values and that no observation equals zero. (Zeros and ties introduce several complications; see below.) The test is performed as follows: 9564: 5604:
distribution where probabilities linearly increase from left to right, Pratt's method outperforms Wilcoxon's. When testing a binomial distribution centered at zero to see whether the parameter of each Bernoulli trial is
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to the observations, with two observations getting the same number if and only if they have the same absolute value. These numbers are conventionally called ranks even though the set of these numbers is not equal to
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The hypothesis that the data are IID can be weakened. Each data point may be taken from a different distribution, as long as all the distributions are assumed to be continuous and symmetric about a common point
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Pratt remarks that, when the signed-rank zero procedure is combined with the average rank procedure for resolving ties, the resulting test is a consistent test against the alternative hypothesis that, for all
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Pratt observed that the reduced sample procedure can lead to paradoxical behavior. He gives the following example. Suppose that we are in the one-sample situation and have the following thirteen observations:
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also returns a logical value indicating the test decision. The result h = 1 indicates a rejection of the null hypothesis, and h = 0 indicates a failure to reject the null hypothesis at the 5% significance
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as small as possible. Pratt observes that when ties are likely, the conservative tiebreaking procedure "presumably has low power, since it amounts to breaking all ties in favor of the null hypothesis."
11191: 11321:, or in this case 45 − 18 = 27. Next, the two rank-sum proportions are 27/45 = 60% and 18/45 = 40%. Finally, the rank correlation is the difference between the two proportions (.60 minus .40), hence 1027: 9569: 8334: 7876: 5186: 2085: 1550: 1266: 5405:, the probability of calling a set of observations significantly positive (respectively, significantly negative) is a non-decreasing (respectively, non-increasing) function of the observations. 5092: 208: 45:
of a population based on a sample of data, or to compare the locations of two populations using two matched samples. The one-sample version serves a purpose similar to that of the one-sample
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Because the one-sample test can be used as a one-sided test for stochastic dominance, the paired difference Wilcoxon test can be used to compare the following hypotheses:
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tend to be more significant, ties are broken by assigning lower ranks to negative observations and higher ranks to positive ones. When the test makes positive values of
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The technical underpinnings of these expansions are rather involved, because conventional Edgeworth expansions apply to sums of IID continuous random variables, while
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Increasing the observed values does not make a significantly positive sample insignificant, and it does not make an insignificant sample significantly negative.
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When zeros are present and the signed-rank zero procedure is used, or when ties are present and the average rank procedure is used, the null distribution of
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This procedure includes the zeros when ranking the observations in the sample. However, it excludes them from the test statistic, or equivalently it defines
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The other common option for handling ties is a tiebreaking procedure. In a tiebreaking procedure, the observations are assigned distinct ranks in the set
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The one-sample Wilcoxon signed-rank test can be used to test whether data comes from a symmetric population with a specified center (which corresponds to
9060: 732: 1428:{\displaystyle {\begin{aligned}T^{+}&=\sum _{1\leq i\leq n,\ X_{i}>0}R_{i},\\T^{-}&=\sum _{1\leq i\leq n,\ X_{i}<0}R_{i}.\end{aligned}}} 3080:. The data points are not required to be independent as long as the conditional distribution of each observation given the others is symmetric about 2235:{\displaystyle {\begin{aligned}T^{+}=\#\{W_{ij}>0\colon 1\leq i\leq j\leq n\},\\T^{-}=\#\{W_{ij}<0\colon 1\leq i\leq j\leq n\}.\end{aligned}}} 12319: 8061: 7393: 5600:
with equally spaced categories, the signed-rank zero procedure is more likely to maintain the Type I error rate than the reduced sample procedure.
9728:. Early authors such as Siegel followed Wilcoxon. This is appropriate for two-sided hypothesis tests, but it cannot be used for one-sided tests. 13830: 5668:
are used to calculate the test statistic. In the presence of ties, the ranks are not defined. There are two main approaches to resolving this.
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The signed-rank zero procedure has the disadvantage that, when zeros occur, the null distribution of the test statistic changes, so tables of
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The average rank procedure can disagree with tiebreaking procedures. Pratt gives the following example. Suppose that the observations are:
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The restriction that the alternative distribution is symmetric is highly restrictive, but for one-sided tests it can be weakened. Say that
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is a sum of non-identically distributed discrete random variables. The final result, however, is that the above expansion has an error of
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The positive-rank sum and negative-rank sum have alternative interpretations that are useful for the theory behind the test. Define the
14109: 12750: 10992:. Notice that pairs 3 and 9 are tied in absolute value. They would be ranked 1 and 2, so each gets the average of those ranks, 1.5. 4599: 4422: 1032: 13883: 2627:. If this median is unique, then the Wilcoxon signed-rank sum test becomes a test for the location of the median. When the mean of 12206:
Cureton, Edward E. (1967). "The normal approximation to the signed-rank sampling distribution when zero differences are present".
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is computed for every possible way of breaking ties, and the final statistic is the mean of the tie-broken statistics. In the
5331:. Pratt proved that the signed-rank zero procedure has several desirable behaviors not shared by the reduced sample procedure: 964: 12344: 12063: 11778: 11624: 12745: 12445: 11255: 11245: 8252:, even the above recursion is too slow. In this case, the null distribution can be approximated. The null distributions of 13349: 12497: 12360: 9177:
changes. Cureton derived a normal approximation for this situation. Suppose that the original number of observations was
8828:{\displaystyle \Pr(T^{+}\leq k)\approx \Phi (t)+\phi (t){\Big (}{\frac {3n^{2}+3n-1}{10n(n+1)(2n+1)}}{\Big )}(t^{3}-3t),} 7788: 5144: 11313:
is 3 + 4 + 5 + 6 = 18. From this information alone, the remaining rank sum can be computed, because it is the total sum
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Better approximations can be produced using Edgeworth expansions. Using a fourth-order Edgeworth expansion shows that:
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because it considers the magnitude of the differences, but it requires this moderately strong assumption of symmetry.
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scale, a type of scale that carries more information than an ordinal scale but may have less than an interval scale.
14737: 14310: 14184: 6771:, the distribution may be computed exactly. Under the null hypothesis that the data is symmetric about zero, each 2846: 2737: 2022: 304:. In general, it must be possible to rank the differences between the pairs. This requires that the data be on an 14368: 14029: 13774: 13145: 12735: 11389: 10014:. When consideration is restricted to continuous distributions, this is a minimum variance unbiased estimator of 14419: 13631: 13438: 13327: 13285: 10998: 638: 38: 13359: 6476:
breaks the ties in favor of the null hypothesis. When performing a one-sided test in which negative values of
5296: 2266:). If the population center is known, then it can be used to test whether data is symmetric about its center. 574: 14662: 13621: 12524: 8180:
with similar boundary conditions. There is also a recursive formula for the cumulative distribution function
4886: 4139: 3997: 3855: 2928:. Then the Wilcoxon signed-rank sum test can also be used for the following null and alternative hypotheses: 364: 12290:
Kerby, Dave S. (2014), "The simple difference formula: An approach to teaching nonparametric correlation.",
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but with the modified ranks in place of the ordinary ranks. The probability that the sum of two independent
435: 210:. Each data point in the sample is a pair of measurements. In the simplest case, the measurements are on an 14213: 14162: 14147: 14137: 14006: 13878: 13845: 13671: 13626: 13456: 5671:
The most common procedure for handling ties, and the one originally recommended by Wilcoxon, is called the
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under the null hypothesis. There is no closed formula for this distribution. However, for small values of
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Kerby, D. S. (2014). The simple difference formula: An approach to teaching nonparametric correlation.
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which is zero and no other zeros or ties.) Because of this, the test statistic needs to be modified.
31: 8953:{\displaystyle t={\frac {k+{\tfrac {1}{2}}-{\frac {n(n+1)}{4}}}{\sqrt {\frac {n(n+1)(2n+1)}{24}}}}.} 7515: 7269: 7187: 7080: 6426: 5687: 14657: 14424: 14287: 13972: 13937: 13901: 13686: 13128: 13037: 12996: 12908: 12599: 12438: 11512: 11334: 7344: 5000:
The reduced sample procedure removes the zero. To the remaining data, it assigns the signed ranks:
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Two other options for handling ties are based around averaging the results of tiebreaking. In the
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includes implementation of the Wilcoxon signed-rank test in C++, C#, Delphi, Visual Basic, etc.
9827: 9795: 5246: 5015: 3925: 3783: 3452: 3374: 2462: 2405: 544:: The rank of the smallest observation is one, the rank of the next smallest is two, and so on. 54: 20: 3083: 3056: 14769: 14629: 14571: 14514: 14340: 14233: 14142: 13868: 13752: 13611: 13603: 13493: 13485: 13300: 13196: 13174: 13133: 13098: 13065: 13011: 12986: 12941: 12880: 12840: 12642: 12465: 12334: 11901:
Conover, William Jay (1973). "On Methods of Handling Ties in the Wilcoxon Signed-Rank Test".
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To explain the null and alternative hypotheses formally, assume that the data consists of
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Derrick, B; White, P (2017). "Comparing Two Samples from an Individual Likert Question".
11487: 11150:{\displaystyle |W|<W_{\operatorname {crit} (\alpha =0.05,\ 9{\text{, two-sided}})}=15} 9738: 6827: 6801: 6539: 6213: 74: 46: 11398:
includes an implementation of the Wilcoxon signed-rank test in C# for .NET applications.
5141:. Therefore the sample would be judged significantly positive at any significance level 4393:
are stochastically smaller than a distribution symmetric about zero, that is, for every
102:(1956) in his influential textbook on non-parametric statistics. Siegel used the symbol 14713: 14524: 14378: 14274: 14223: 14099: 13996: 13980: 13957: 13734: 13468: 13451: 13411: 13322: 13217: 13179: 13150: 13110: 13070: 13016: 12933: 12619: 12614: 11543: 11199: 10427: 10058: 9933: 9859: 9285: 9265: 9200: 9180: 9160: 9040: 8255: 8235: 7998: 7664: 7644: 7580: 6950: 6903: 6880: 6754: 6734: 6686: 6519: 6499: 6479: 6319: 6299: 6279: 6239: 6193: 5569: 5549: 4570:
are stochastically larger than a distribution symmetric about zero, that is, for every
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The data for a one-sample test is a sample in which each observation is a real number:
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Pratt, J. (1959). "Remarks on zeros and ties in the Wilcoxon signed rank procedures".
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is exactly as likely to be positive as it is negative. Therefore the probability that
4279:, and therefore, under the null hypothesis, the distribution is symmetric about zero. 2313:
can be assumed symmetric, then the null and alternative hypotheses are the following:
14708: 14619: 14589: 14581: 14401: 14392: 14317: 14248: 14104: 14089: 14064: 13952: 13893: 13759: 13747: 13373: 13290: 13234: 13157: 13001: 12923: 12702: 12576: 12340: 12313: 12173: 12156: 12059: 11774: 11682: 11620: 11568: 11466: 11401: 11293:= (1 + 2 + 3 + 4 + 5 + 6 + 7 + 8 + 9) = 45. Hence, the rank correlation is 9/45, so 14644: 14599: 14363: 14350: 14243: 14218: 14152: 14084: 13962: 13570: 13463: 13396: 13309: 13256: 13075: 12946: 12740: 12624: 12539: 12506: 12299: 12219: 12215: 12168: 11914: 11910: 11850: 11846: 11535: 11527: 11412: 5047:, and therefore the sample is not significantly positive at any significance level 106:
for the test statistic, and consequently, the test is sometimes referred to as the
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under the null hypothesis is equal to the number of sign combinations that yield
5896:{\displaystyle |X_{3}|<|X_{2}|=|X_{5}|<|X_{6}|<|X_{1}|=|X_{4}|=|X_{7}|.} 14051: 4817:. It can also happen that there are tied observations. This means that for some 14510: 14505: 12968: 12898: 12544: 11422: 10958: 703: 211: 91: 69:-test for dependent samples"). The Wilcoxon test is a good alternative to the 11539: 6516:
significant, ties are broken the other way, and when large absolute values of
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carry the same information, any of them may be used as the test statistic.
12410:- Nonparametric effect size estimators (Copyright 2015 by Karl L. Weunsch) 6711:-value is computed for every possible way of breaking ties, and the final 3557:
These can also be expressed more directly in terms of the original pairs:
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implements various one-tailed and two-tailed versions of the test in the
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If the distribution of the observations is symmetric, then the values of
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includes an implementation of the Wilcoxon signed-rank test in Python.
13651: 13503: 13123: 12918: 12830: 12815: 12810: 12775: 11441: 9423:{\displaystyle \mathbf {E} ={\frac {n(n+1)}{4}}-{\frac {z(z+1)}{4}}.} 79: 34: 11531: 13167: 12785: 12662: 12657: 12652: 11265:
is reported, the rank correlation r is equal to the test statistic
6967:. However, there is an efficient recursion for the distribution of 3017:
is stochastically smaller than a distribution symmetric about zero.
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HypothesisTests package includes the Wilcoxon signed-rank test as
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Wilcoxon originally defined the Wilcoxon rank-sum statistic to be
9148:{\displaystyle M(t)={\frac {1}{2^{n}}}\prod _{j=1}^{n}(1+e^{jt}).} 3048:
is stochastically larger than a distribution symmetric about zero.
14672: 14373: 10989: 801:{\displaystyle T=\sum _{i=1}^{N}\operatorname {sgn}(X_{i})R_{i}.} 6627:. On the other hand, any tiebreaking rule will assign the ranks 4704:
In real data, it sometimes happens that there is an observation
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that the median of pairwise differences is different from zero.
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stochastically smaller than a distribution symmetric about zero
2255: 70: 9950:-distributed random variables is positive can be estimated as 7758:. Under the null hypothesis, the probability mass function of 4688:{\displaystyle Pr(X_{i}<Y_{i}-x)\leq \Pr(X_{i}>Y_{i}+x)} 4511:{\displaystyle Pr(X_{i}<Y_{i}-x)\geq \Pr(X_{i}>Y_{i}+x)} 2841:
stochastically larger than a distribution symmetric about zero
1106:{\displaystyle |X_{\sigma (1)}|<\dots <|X_{\sigma (n)}|} 12423: 9034:, just like a conventional fourth-order Edgeworth expansion. 8173:{\displaystyle 2p_{n}(t^{+})=p_{n-1}(t^{+})+p_{n-1}(t^{+}-n)} 7505:{\displaystyle u_{n}(t^{+})=u_{n-1}(t^{+})+u_{n-1}(t^{+}-n).} 6586:
This sample is significantly positive at the one-sided level
6356:. The average rank procedure therefore assigns them the rank 94:(1892–1965) who, in a single paper, proposed both it and the 12403:
A table of critical values for the Wilcoxon signed-rank test
2667:, and the test is also a test for the location of the mean. 12514: 5546:
differ by at least a fixed constant that is independent of
5385:, and for a test which is randomized to have level exactly 2259: 12339:. Springer Science & Business Media. pp. 99–100. 11186:{\displaystyle \therefore {\text{failed to reject }}H_{0}} 6578:
The average rank procedure assigns these the signed ranks
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an insignificant sample causes it to appear significantly
6296:. If the ties among the observations with absolute value 3240:. In this case, the null and alternative hypotheses are: 98:
for two independent samples. The test was popularized by
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Brief guide by experimental psychologist Karl L. Weunsch
6877:. This can be used to compute the exact distribution of 6316:
were broken, then these observations would occupy ranks
5098:−1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, −13. 1022:{\displaystyle \sigma :\{1,\dots ,n\}\to \{1,\dots ,n\}} 126:
For a paired sample test, the data consists of a sample
12157:"Edgeworth approximations for rank sum test statistics" 11759: 11404:
implements this test using "Wilcoxon rank sum test" as
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of each group of tied observations. The expectation of
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observations have absolute value less than or equal to
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Non-parametric statistics for the behavioral sciences
11222: 11202: 11164: 11082: 11001: 10967: 10941: 10917: 10646: 10618: 10595: 10574: 10519: 10485: 10451: 10430: 10226: 10205: 10150: 10116: 10082: 10061: 10020: 9956: 9936: 9909: 9882: 9862: 9830: 9798: 9771: 9741: 9685: 9567: 9436: 9335: 9308: 9288: 9268: 9223: 9203: 9183: 9163: 9063: 9043: 8993: 8966: 8841: 8652: 8332: 8305: 8278: 8258: 8238: 8186: 8064: 8021: 8001: 7961: 7918: 7884: 7791: 7764: 7731: 7687: 7667: 7647: 7603: 7583: 7556: 7518: 7396: 7347: 7321: 7272: 7239: 7190: 7148: 7121: 7083: 7043: 7000: 6973: 6953: 6926: 6906: 6883: 6856: 6830: 6804: 6777: 6757: 6737: 6689: 6641: 6592: 6542: 6522: 6502: 6482: 6429: 6406: 6362: 6342: 6322: 6302: 6282: 6262: 6242: 6216: 6196: 6144: 6117: 6090: 6063: 6036: 5990: 5963: 5936: 5909: 5731: 5690: 5647: 5610: 5572: 5552: 5497: 5442: 5416: 5391: 5371: 5344: 5299: 5249: 5214: 5194: 5147: 5112: 5053: 5018: 4955: 4889: 4849: 4823: 4783: 4737: 4710: 4602: 4576: 4536: 4425: 4399: 4359: 4301: 4245: 4205: 4142: 4096: 4070: 4000: 3954: 3928: 3858: 3812: 3786: 3718: 3672: 3626: 3576: 3533: 3493: 3455: 3415: 3377: 3337: 3299: 3259: 3200: 3165: 3122: 3086: 3059: 3034: 3003: 2966: 2946: 2908: 2849: 2825: 2799: 2740: 2720: 2700: 2676: 2653: 2633: 2613: 2593: 2552: 2522: 2502: 2465: 2445: 2408: 2388: 2351: 2331: 2299: 2279: 2083: 2025: 1995: 1962: 1935: 1915: 1548: 1481: 1441: 1264: 1237: 1207: 1198:
is closely related to two other test statistics. The
1184: 1161: 1119: 1035: 967: 907: 887: 860: 836: 816: 735: 715: 682: 641: 615: 577: 553: 504: 438: 367: 317: 270: 224: 132: 14336:
Autoregressive conditional heteroskedasticity (ARCH)
11246:
Mann–Whitney_U_test § Rank-biserial_correlation
9735:, it is also possible to assign ranks between 0 and 8326:
are asymptotically normal with means and variances:
6947:
sums, which is intractable for all but the smallest
6920:
by considering all possibilities requires computing
6850:
divided by the number of possible sign combinations
11884:
International Journal of Mathematics and Statistics
7871:{\displaystyle \Pr(T^{+}=t^{+})=u_{n}(t^{+})/2^{n}} 5725:For example, suppose that the observations satisfy 5181:{\displaystyle \alpha >109/2^{13}\approx 0.0133} 13798: 12054:Gibbons, Jean D.; Chakraborti, Subhabrata (2011). 12053: 11289:= 9. The sample size of 9 has a total rank sum of 11285:. Using the above example, the test statistic is 11228: 11208: 11185: 11149: 11067: 10980: 10949: 10923: 10665: 10631: 10603: 10580: 10557: 10504: 10470: 10436: 10234: 10211: 10188: 10135: 10101: 10067: 10033: 10006: 9942: 9922: 9895: 9868: 9848: 9816: 9784: 9753: 9720: 9664: 9553: 9422: 9321: 9294: 9274: 9254: 9209: 9189: 9169: 9147: 9049: 9026: 8979: 8952: 8827: 8636: 8318: 8291: 8264: 8244: 8221: 8172: 8050: 8007: 7987: 7947: 7897: 7870: 7777: 7750: 7717: 7673: 7653: 7633: 7589: 7569: 7542: 7504: 7382: 7333: 7307: 7258: 7225: 7176: 7134: 7107: 7069: 7029: 6986: 6959: 6939: 6912: 6889: 6869: 6842: 6816: 6790: 6763: 6743: 6722: 6695: 6668: 6619: 6558: 6528: 6508: 6488: 6453: 6412: 6388: 6348: 6328: 6308: 6288: 6268: 6248: 6228: 6202: 6182: 6130: 6103: 6076: 6049: 6022: 5976: 5949: 5922: 5895: 5714: 5660: 5625: 5578: 5558: 5538: 5483: 5428: 5397: 5377: 5350: 5323: 5270: 5235: 5200: 5180: 5133: 5087:{\displaystyle \alpha <55/2^{12}\approx 0.0134} 5086: 5039: 4996:0, 2, 3, 4, 6, 7, 8, 9, 11, 14, 15, 17, −18. 4968: 4941: 4875: 4835: 4809: 4769: 4723: 4687: 4588: 4562: 4510: 4411: 4385: 4333: 4271: 4231: 4186: 4128: 4082: 4044: 3986: 3940: 3902: 3844: 3798: 3760: 3704: 3658: 3608: 3545: 3519: 3467: 3441: 3389: 3363: 3311: 3285: 3232: 3194:be the joint cumulative distribution of the pairs 3186: 3148: 3099: 3072: 3040: 3009: 2978: 2952: 2920: 2894: 2831: 2811: 2785: 2726: 2706: 2682: 2659: 2639: 2619: 2599: 2579: 2534: 2508: 2477: 2451: 2420: 2394: 2363: 2337: 2305: 2285: 2244: 2234: 2069: 2011: 1975: 1948: 1921: 1901: 1534: 1467: 1427: 1250: 1220: 1190: 1167: 1147: 1105: 1021: 953: 893: 873: 842: 822: 800: 721: 694: 668: 627: 601: 559: 536: 490: 422: 349: 296: 256: 203:{\displaystyle (X_{1},Y_{1}),\dots ,(X_{n},Y_{n})} 202: 8792: 8710: 6420:which the test does not reject form an interval. 14751: 9686: 8653: 8187: 7792: 7037:to be the number of sign combinations for which 5498: 5443: 5358:which the test does not reject form an interval. 4647: 4470: 2874: 2850: 2765: 2741: 2553: 13884:Multivariate adaptive regression splines (MARS) 12208:Journal of the American Statistical Association 11903:Journal of the American Statistical Association 11839:Journal of the American Statistical Association 10666:{\displaystyle \operatorname {sgn} \cdot R_{i}} 6536:are significant, ties are broken so as to make 12417:, volume 3, article 1. doi:10.2466/11.IT.3.1. 12393:Example of using the Wilcoxon signed-rank test 11773:(Third ed.). John Wiley & Sons, Inc. 11676: 11670: 850:to its distribution under the null hypothesis. 12439: 11824:Some Rapid Approximate Statistical Procedures 6731:-values requires knowing the distribution of 5679:This procedure assigns numbers between 1 and 5004:1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, −12. 12318:: CS1 maint: DOI inactive as of June 2024 ( 12285: 12283: 11881: 11614: 11465:(3rd ed.). John Wiley & Sons, Inc. 11370:, where x and y are vectors of equal length. 7712: 7688: 7628: 7604: 7537: 7519: 7512:The formula is true because every subset of 7102: 7084: 7077:. This is equal to the number of subsets of 6448: 6430: 5709: 5691: 5641:When the data does not have ties, the ranks 2895:{\displaystyle \Pr(X<-x)\leq \Pr(X>x)} 2786:{\displaystyle \Pr(X<-x)\geq \Pr(X>x)} 2222: 2176: 2150: 2104: 2070:{\displaystyle {\tfrac {1}{2}}(X_{i}+X_{j})} 1016: 998: 992: 974: 12097:Pratt and Gibbons, pp. 148–149, pp. 186–187 11875: 11769:; Wolfe, Douglas A.; Chicken, Eric (2014). 11513:"Individual comparisons by ranking methods" 11328: 6236:observations have absolute value less than 498:, and use this sorted list to assign ranks 12484: 12446: 12432: 12361:"Wilcox signed-rank test: SAS instruction" 12150: 12148: 12058:(Fifth ed.). Chapman & Hall/CRC. 11337:includes an implementation of the test as 11254:for the signed-rank test, one can use the 4731:in the sample which equals zero or a pair 3712:have the same distribution. Equivalently, 1475:equals the sum of all the ranks, which is 13097: 12303: 12280: 12172: 11615:Pratt, John W.; Gibbons, Jean D. (1981). 11567:. New York: McGraw-Hill. pp. 75–83. 11068:{\displaystyle W=1.5+1.5-3-4-5-6+7+8+9=9} 9731:Instead of assigning ranks between 1 and 9674: 7995:under the null hypothesis when there are 5633:, Wilcoxon's method outperforms Pratt's. 1542:, these three statistics are related by: 669:{\displaystyle \operatorname {sgn}(x)=-1} 12332: 11821: 11510: 11309:is the smaller of the two rank sums, so 9302:is still zero, while the expectation of 5324:{\displaystyle \operatorname {sgn}(0)=0} 602:{\displaystyle \operatorname {sgn}(x)=1} 12205: 12199: 12154: 12145: 11900: 11504: 11460: 7597:, in which case it is also a subset of 4942:{\displaystyle X_{i}-Y_{i}=X_{j}-Y_{j}} 4187:{\displaystyle (Y_{i}+\mu ,X_{i}-\mu )} 4045:{\displaystyle (Y_{i}+\mu ,X_{i}-\mu )} 3903:{\displaystyle (Y_{i}+\mu ,X_{i}-\mu )} 2271:independent and identically distributed 423:{\displaystyle |X_{1}|,\dots ,|X_{n}|.} 14752: 14410:Kaplan–Meier estimator (product limit) 11560: 11454: 7142:. The base cases of the recursion are 491:{\displaystyle |X_{1}|,\dots ,|X_{n}|} 14483: 14050: 13797: 13096: 12866: 12483: 12427: 12289: 11836: 11830: 11554: 9824:, and the modified negative-rank sum 7681:from the subset produces a subset of 6715:-value is the mean of the tie-broken 5539:{\displaystyle \Pr(X_{i}+X_{j}<0)} 5484:{\displaystyle \Pr(X_{i}+X_{j}>0)} 4985:were no ties. This is now called the 1535:{\displaystyle 1+2+\dots +n=n(n+1)/2} 14720: 14420:Accelerated failure time (AFT) model 11679:Statistical Inference Based on Ranks 10924:{\displaystyle \operatorname {sgn} } 10581:{\displaystyle \operatorname {sgn} } 10212:{\displaystyle \operatorname {sgn} } 9262:where the sum is over all the sizes 8222:{\displaystyle \Pr(T^{+}\leq t^{+})} 560:{\displaystyle \operatorname {sgn} } 14732: 14015:Analysis of variance (ANOVA, anova) 12867: 12056:Nonparametric Statistical Inference 10007:{\displaystyle 2T_{0}^{+}/(n(n-1))} 6582:2.5, 2.5, 2.5, 2.5, 5, 6, −7. 5365:For a fixed significance threshold 3110: 954:{\displaystyle |X_{j}|\leq |X_{i}|} 53:. For two matched samples, it is a 13: 14110:Cochran–Mantel–Haenszel statistics 12736:Pearson product-moment correlation 12161:Statistics and Probability Letters 11677:Hettmansperger, Thomas P. (1984). 11463:Practical nonparametric statistics 9037:The moment generating function of 8681: 7905:is closely related to the integer 2249: 2173: 2101: 537:{\displaystyle R_{1},\dots ,R_{n}} 350:{\displaystyle X_{1},\dots ,X_{n}} 14: 14781: 12381: 11771:Nonparametric Statistical Methods 9792:, the modified positive-rank sum 9721:{\displaystyle \min(T^{+},T^{-})} 8015:observations in the sample, then 4699: 4521:One-sided alternative hypothesis 4344:One-sided alternative hypothesis 4055:Two-sided alternative hypothesis 3913:One-sided alternative hypothesis 3771:One-sided alternative hypothesis 3478:Two-sided alternative hypothesis 3400:One-sided alternative hypothesis 3322:One-sided alternative hypothesis 3020:One-sided alternative hypothesis 2989:One-sided alternative hypothesis 2488:Two-sided alternative hypothesis 2431:One-sided alternative hypothesis 2374:One-sided alternative hypothesis 117: 14731: 14719: 14707: 14694: 14693: 14484: 11617:Concepts of Nonparametric Theory 9337: 8424: 8366: 8338: 7718:{\displaystyle \{1,\dots ,n-1\}} 7634:{\displaystyle \{1,\dots ,n-1\}} 6669:{\displaystyle \alpha =14/2^{7}} 6620:{\displaystyle \alpha =14/2^{7}} 1148:{\displaystyle R_{\sigma (i)}=i} 214:. Then they may be converted to 14369:Least-squares spectral analysis 12353: 12326: 12271: 12262: 12253: 12244: 12235: 12226: 12190: 12181: 12136: 12127: 12118: 12109: 12100: 12091: 12082: 12073: 12047: 12038: 12029: 12020: 12011: 12002: 11999:Pratt and Gibbons, pp. 163, 166 11993: 11984: 11975: 11966: 11957: 11948: 11939: 11930: 11921: 11894: 11866: 11857: 11815: 11806: 11797: 11788: 11750: 11741: 11732: 11723: 11714: 11705: 11696: 11661: 11652: 11643: 11416: 11405: 11338: 10558:{\displaystyle x_{2,i}-x_{1,i}} 10189:{\displaystyle x_{2,i}-x_{1,i}} 9765:. The modified signed-rank sum 9255:{\displaystyle c=\sum t^{3}-t,} 8058:satisfies a similar recursion: 6723:Computing the null distribution 5626:{\displaystyle {\tfrac {1}{2}}} 5593:-values can no longer be used. 2245:Null and alternative hypotheses 13350:Mean-unbiased minimum-variance 12453: 12388:Wilcoxon Signed-Rank Test in R 12336:Introductory Statistics with R 12220:10.1080/01621459.1967.10500917 12088:Pratt and Gibbons, pp. 148–149 11972:Pratt and Gibbons, pp. 168–169 11915:10.1080/01621459.1973.10481460 11851:10.1080/01621459.1959.10501526 11729:Pratt and Gibbons, pp. 155–156 11702:Pratt and Gibbons, pp. 146–147 11634: 11608: 11599: 11590: 11581: 11480: 11269:divided by the total rank sum 11239: 11136: 11110: 11092: 11084: 10001: 9998: 9986: 9980: 9715: 9689: 9630: 9617: 9584: 9578: 9525: 9510: 9507: 9495: 9486: 9471: 9468: 9456: 9408: 9396: 9378: 9366: 9354: 9341: 9139: 9117: 9073: 9067: 9021: 8997: 8936: 8921: 8918: 8906: 8890: 8878: 8819: 8797: 8784: 8769: 8766: 8754: 8705: 8699: 8690: 8684: 8675: 8656: 8618: 8603: 8600: 8588: 8572: 8566: 8544: 8529: 8526: 8514: 8502: 8489: 8473: 8460: 8434: 8428: 8407: 8395: 8383: 8370: 8355: 8342: 8216: 8190: 8167: 8148: 8126: 8113: 8091: 8078: 8045: 8032: 7942: 7929: 7850: 7837: 7821: 7795: 7543:{\displaystyle \{1,\dots ,n\}} 7496: 7477: 7455: 7442: 7420: 7407: 7369: 7357: 7308:{\displaystyle u_{n}(t^{+})=0} 7296: 7283: 7226:{\displaystyle u_{0}(t^{+})=0} 7214: 7201: 7165: 7159: 7108:{\displaystyle \{1,\dots ,n\}} 7024: 7011: 6900:Computing the distribution of 6552: 6544: 6454:{\displaystyle \{1,\dots ,n\}} 6375: 6363: 6163: 6145: 6003: 5991: 5886: 5871: 5863: 5848: 5840: 5825: 5817: 5802: 5794: 5779: 5771: 5756: 5748: 5733: 5715:{\displaystyle \{1,\dots ,n\}} 5533: 5501: 5478: 5446: 5312: 5306: 4764: 4738: 4682: 4650: 4641: 4609: 4505: 4473: 4464: 4432: 4328: 4302: 4181: 4143: 4123: 4097: 4039: 4001: 3981: 3955: 3897: 3859: 3839: 3813: 3755: 3743: 3734: 3722: 3699: 3673: 3653: 3627: 3603: 3577: 3227: 3201: 3181: 3169: 2889: 2877: 2868: 2853: 2780: 2768: 2759: 2744: 2568: 2556: 2064: 2038: 1867: 1855: 1837: 1825: 1738: 1726: 1695: 1683: 1631: 1619: 1588: 1576: 1521: 1509: 1134: 1128: 1099: 1093: 1087: 1075: 1061: 1055: 1049: 1037: 995: 947: 932: 924: 909: 854:The ranks are defined so that 782: 769: 654: 648: 590: 584: 484: 469: 455: 440: 413: 398: 384: 369: 251: 225: 197: 171: 159: 133: 39:statistical hypothesis testing 1: 14663:Geographic information system 13879:Simultaneous equations models 12398:An online version of the test 11447: 10418:order by absolute difference 7383:{\displaystyle t>n(n+1)/2} 5289:Pratt therefore proposed the 4770:{\displaystyle (X_{i},Y_{i})} 4334:{\displaystyle (X_{i},Y_{i})} 4239:has the same distribution as 4129:{\displaystyle (X_{i},Y_{i})} 3987:{\displaystyle (X_{i},Y_{i})} 3845:{\displaystyle (X_{i},Y_{i})} 3761:{\displaystyle F(x,y)=F(y,x)} 3705:{\displaystyle (Y_{i},X_{i})} 3659:{\displaystyle (X_{i},Y_{i})} 3609:{\displaystyle (X_{i},Y_{i})} 3233:{\displaystyle (X_{i},Y_{i})} 2714:-distributed random variable 2647:is defined, then the mean is 2580:{\displaystyle \Pr(X=\mu )=0} 257:{\displaystyle (X_{i},Y_{i})} 65:-test for matched pairs" or " 13846:Coefficient of determination 13457:Uniformly most powerful test 12174:10.1016/0167-7152(95)00164-H 11511:Wilcoxon, Frank (Dec 1945). 10950:{\displaystyle {\text{abs}}} 10604:{\displaystyle {\text{abs}}} 10235:{\displaystyle {\text{abs}}} 9197:and the number of zeros was 8051:{\displaystyle p_{n}(t^{+})} 7948:{\displaystyle p_{n}(t^{+})} 7030:{\displaystyle u_{n}(t^{+})} 6635:At the same one-sided level 4883:(in the one-sample case) or 2273:samples from a distribution 7: 14415:Proportional hazards models 14359:Spectral density estimation 14341:Vector autoregression (VAR) 13775:Maximum posterior estimator 13007:Randomized controlled trial 11430: 11417:value(SignedRankTest(x, y)) 10048: 9856:are defined analogously to 9027:{\displaystyle O(n^{-3/2})} 7988:{\displaystyle T^{+}=t^{+}} 7390:. The recursive formula is 7259:{\displaystyle t^{+}\neq 0} 7070:{\displaystyle T^{+}=t^{+}} 6897:under the null hypothesis. 6683:method, the test statistic 6676:, this is not significant. 6631:1, 2, 3, 4, 5, 6, −7. 6574:1, 1, 1, 1, 2, 3, −4. 6389:{\displaystyle (k+\ell )/2} 6183:{\displaystyle (5+6+7)/3=6} 6023:{\displaystyle (2+3)/2=2.5} 5291:signed-rank zero procedure. 4876:{\displaystyle X_{i}=X_{j}} 4810:{\displaystyle X_{i}=Y_{i}} 4563:{\displaystyle X_{i}-Y_{i}} 4386:{\displaystyle X_{i}-Y_{i}} 4272:{\displaystyle Y_{i}-X_{i}} 4232:{\displaystyle X_{i}-Y_{i}} 4194:have the same distribution. 4052:have the same distribution. 3910:have the same distribution. 3520:{\displaystyle X_{i}-Y_{i}} 3442:{\displaystyle X_{i}-Y_{i}} 3364:{\displaystyle X_{i}-Y_{i}} 3286:{\displaystyle X_{i}-Y_{i}} 3149:{\displaystyle X_{i}-Y_{i}} 1468:{\displaystyle T^{+}+T^{-}} 297:{\displaystyle X_{i}-Y_{i}} 16:Statistical hypothesis test 10: 14786: 14175:Multivariate distributions 12595:Average absolute deviation 11437:Mann–Whitney–Wilcoxon test 11243: 11216:-value for this result is 10044: 7177:{\displaystyle u_{0}(0)=1} 5236:{\displaystyle 109/2^{13}} 5188:. The paradox is that, if 5134:{\displaystyle 109/2^{13}} 4083:{\displaystyle \mu \neq 0} 3546:{\displaystyle \mu \neq 0} 2535:{\displaystyle \mu \neq 0} 85: 61:-test (also known as the " 57:like the paired Student's 18: 14689: 14643: 14580: 14533: 14496: 14492: 14479: 14451: 14433: 14400: 14391: 14349: 14296: 14257: 14206: 14197: 14163:Structural equation model 14118: 14075: 14071: 14046: 14005: 13971: 13925: 13892: 13854: 13821: 13817: 13793: 13733: 13642: 13561: 13525: 13516: 13499:Score/Lagrange multiplier 13484: 13437: 13382: 13308: 13299: 13109: 13105: 13092: 13051: 13025: 12977: 12932: 12914:Sample size determination 12879: 12875: 12862: 12766: 12721: 12695: 12677: 12633: 12585: 12505: 12496: 12492: 12479: 12461: 12277:Pratt and Gibbons, p. 191 12268:Pratt and Gibbons, p. 159 12259:Pratt and Gibbons, p. 158 12232:Pratt and Gibbons, p. 193 12155:Kolassa, John E. (1995). 12142:Pratt and Gibbons, p. 149 12133:Pratt and Gibbons, p. 187 12124:Pratt and Gibbons, p. 187 12115:Pratt and Gibbons, p. 187 12026:Pratt and Gibbons, p. 171 12017:Pratt and Gibbons, p. 166 11990:Pratt and Gibbons, p. 170 11945:Pratt and Gibbons, p. 164 11927:Pratt and Gibbons, p. 162 11812:Hettmansperger, pp. 49–50 11803:Pratt and Gibbons, p. 147 11794:Pratt and Gibbons, p. 147 11747:Pratt and Gibbons, p. 155 11738:Hettmansperger, pp. 49–50 11711:Hettmansperger, pp. 30–31 11681:. John Wiley & Sons. 11658:Pratt and Gibbons, p. 150 11649:Pratt and Gibbons, p. 148 11640:Pratt and Gibbons, p. 148 11256:rank-biserial correlation 10513: 10479: 10445: 10424: 10144: 10110: 10076: 10055: 9849:{\displaystyle T_{0}^{-}} 9817:{\displaystyle T_{0}^{+}} 7661:, in which case removing 5271:{\displaystyle 55/2^{12}} 5040:{\displaystyle 55/2^{12}} 4987:reduced sample procedure. 3941:{\displaystyle \mu >0} 3799:{\displaystyle \mu <0} 3468:{\displaystyle \mu >0} 3390:{\displaystyle \mu <0} 2478:{\displaystyle \mu >0} 2421:{\displaystyle \mu <0} 28:Wilcoxon signed-rank test 14765:Nonparametric statistics 14658:Environmental statistics 14180:Elliptical distributions 13973:Generalized linear model 13902:Simple linear regression 13672:Hodges–Lehmann estimator 13129:Probability distribution 13038:Stochastic approximation 12600:Coefficient of variation 12415:Comprehensive Psychology 12333:Dalgaard, Peter (2008). 12292:Comprehensive Psychology 11822:Wilcoxon, Frank (1949). 11329:Software implementations 9217:. The tie correction is 7955:is the probability that 7577:either does not contain 6474:Conservative tiebreaking 6057:is assigned rank 4, and 4979: 3100:{\displaystyle \mu _{0}} 3073:{\displaystyle \mu _{0}} 90:The test is named after 41:used either to test the 19:Not to be confused with 14318:Cross-correlation (XCF) 13926:Non-standard predictors 13360:Lehmann–Scheffé theorem 13033:Adaptive clinical trial 11561:Siegel, Sidney (1956). 11492:www.biostathandbook.com 11461:Conover, W. J. (1999). 10505:{\displaystyle x_{1,i}} 10471:{\displaystyle x_{2,i}} 10136:{\displaystyle x_{1,i}} 10102:{\displaystyle x_{2,i}} 9057:has the exact formula: 7751:{\displaystyle t^{+}-n} 5636: 5429:{\displaystyle i\neq j} 5398:{\displaystyle \alpha } 5378:{\displaystyle \alpha } 5201:{\displaystyle \alpha } 4836:{\displaystyle i\neq j} 4589:{\displaystyle x\geq 0} 4412:{\displaystyle x\geq 0} 2921:{\displaystyle x\geq 0} 2812:{\displaystyle x\geq 0} 14714:Mathematics portal 14535:Engineering statistics 14443:Nelson–Aalen estimator 14020:Analysis of covariance 13907:Ordinary least squares 13831:Pearson product-moment 13235:Statistical functional 13146:Empirical distribution 12979:Controlled experiments 12708:Frequency distribution 12486:Descriptive statistics 12106:Hettmansperger, p. 171 11826:. American Cynamic Co. 11300:If the test statistic 11261:If the test statistic 11230: 11229:{\displaystyle 0.6113} 11210: 11187: 11170:failed to reject  11151: 11069: 10982: 10951: 10925: 10667: 10633: 10605: 10582: 10559: 10506: 10472: 10438: 10236: 10213: 10190: 10137: 10103: 10069: 10035: 10008: 9944: 9924: 9897: 9870: 9850: 9818: 9786: 9755: 9722: 9675:Alternative statistics 9666: 9555: 9424: 9323: 9296: 9276: 9256: 9211: 9191: 9171: 9149: 9116: 9051: 9028: 8981: 8954: 8829: 8638: 8320: 8293: 8266: 8246: 8223: 8174: 8052: 8009: 7989: 7949: 7899: 7872: 7779: 7752: 7719: 7675: 7655: 7635: 7591: 7571: 7544: 7506: 7384: 7335: 7334:{\displaystyle t<0} 7309: 7260: 7227: 7178: 7136: 7109: 7071: 7031: 6988: 6961: 6941: 6914: 6891: 6871: 6844: 6818: 6792: 6765: 6745: 6697: 6670: 6621: 6560: 6530: 6510: 6490: 6455: 6414: 6390: 6350: 6330: 6310: 6290: 6270: 6250: 6230: 6204: 6184: 6132: 6105: 6078: 6051: 6024: 5978: 5951: 5924: 5897: 5716: 5662: 5627: 5596:When the data is on a 5580: 5560: 5540: 5485: 5430: 5399: 5379: 5352: 5325: 5272: 5237: 5202: 5182: 5135: 5088: 5041: 4970: 4943: 4877: 4837: 4811: 4771: 4725: 4689: 4590: 4564: 4512: 4413: 4387: 4335: 4273: 4233: 4188: 4130: 4084: 4046: 3988: 3942: 3904: 3846: 3800: 3762: 3706: 3660: 3610: 3547: 3521: 3469: 3443: 3391: 3365: 3313: 3312:{\displaystyle \mu =0} 3287: 3234: 3188: 3187:{\displaystyle F(x,y)} 3150: 3101: 3074: 3042: 3011: 2980: 2979:{\displaystyle \mu =0} 2954: 2922: 2896: 2833: 2813: 2787: 2728: 2708: 2684: 2661: 2641: 2621: 2601: 2581: 2536: 2510: 2479: 2453: 2422: 2396: 2365: 2364:{\displaystyle \mu =0} 2339: 2307: 2287: 2236: 2071: 2013: 2012:{\displaystyle W_{ij}} 1977: 1950: 1923: 1903: 1536: 1469: 1429: 1252: 1222: 1192: 1169: 1149: 1107: 1023: 955: 895: 875: 844: 824: 802: 762: 723: 696: 695:{\displaystyle x<0} 670: 629: 628:{\displaystyle x>0} 603: 561: 538: 492: 424: 351: 298: 258: 204: 55:paired difference test 21:Wilcoxon rank-sum test 14630:Population statistics 14572:System identification 14306:Autocorrelation (ACF) 14234:Exponential smoothing 14148:Discriminant analysis 14143:Canonical correlation 14007:Partition of variance 13869:Regression validation 13713:(Jonckheere–Terpstra) 13612:Likelihood-ratio test 13301:Frequentist inference 13213:Location–scale family 13134:Sampling distribution 13099:Statistical inference 13066:Cross-sectional study 13053:Observational studies 13012:Randomized experiment 12841:Stem-and-leaf display 12643:Central limit theorem 12308:(inactive 2024-06-26) 12196:Hettmansperger, p. 35 12187:Hettmansperger, p. 37 12079:Hettmansperger, p. 34 11231: 11211: 11188: 11152: 11070: 10983: 10981:{\displaystyle R_{i}} 10952: 10926: 10668: 10634: 10632:{\displaystyle R_{i}} 10606: 10583: 10560: 10507: 10473: 10439: 10237: 10214: 10191: 10138: 10104: 10070: 10036: 10034:{\displaystyle p_{2}} 10009: 9945: 9925: 9923:{\displaystyle T^{-}} 9898: 9896:{\displaystyle T^{+}} 9871: 9851: 9819: 9787: 9785:{\displaystyle T_{0}} 9756: 9723: 9667: 9556: 9425: 9324: 9322:{\displaystyle T^{+}} 9297: 9277: 9257: 9212: 9192: 9172: 9150: 9096: 9052: 9029: 8982: 8980:{\displaystyle T^{+}} 8955: 8830: 8639: 8321: 8319:{\displaystyle T^{-}} 8294: 8292:{\displaystyle T^{+}} 8267: 8247: 8224: 8175: 8053: 8010: 7990: 7950: 7900: 7898:{\displaystyle u_{n}} 7873: 7780: 7778:{\displaystyle T^{+}} 7753: 7720: 7676: 7656: 7641:, or it does contain 7636: 7592: 7572: 7570:{\displaystyle t^{+}} 7545: 7507: 7385: 7336: 7310: 7261: 7228: 7179: 7137: 7135:{\displaystyle t^{+}} 7110: 7072: 7032: 6989: 6987:{\displaystyle T^{+}} 6962: 6942: 6940:{\displaystyle 2^{n}} 6915: 6892: 6872: 6870:{\displaystyle 2^{n}} 6845: 6819: 6793: 6791:{\displaystyle X_{i}} 6766: 6746: 6698: 6671: 6622: 6561: 6531: 6511: 6491: 6456: 6415: 6391: 6351: 6349:{\displaystyle \ell } 6331: 6311: 6291: 6271: 6269:{\displaystyle \ell } 6251: 6231: 6205: 6185: 6133: 6131:{\displaystyle X_{7}} 6106: 6104:{\displaystyle X_{4}} 6079: 6077:{\displaystyle X_{1}} 6052: 6050:{\displaystyle X_{6}} 6025: 5979: 5977:{\displaystyle X_{5}} 5952: 5950:{\displaystyle X_{2}} 5925: 5923:{\displaystyle X_{3}} 5898: 5717: 5663: 5661:{\displaystyle R_{i}} 5628: 5581: 5561: 5541: 5486: 5431: 5400: 5380: 5353: 5326: 5273: 5238: 5203: 5183: 5136: 5102:This has a one-sided 5089: 5042: 5008:This has a one-sided 4971: 4969:{\displaystyle X_{i}} 4944: 4878: 4838: 4812: 4772: 4726: 4724:{\displaystyle X_{i}} 4690: 4591: 4565: 4513: 4414: 4388: 4336: 4274: 4234: 4189: 4131: 4085: 4047: 3989: 3943: 3905: 3847: 3801: 3763: 3707: 3661: 3611: 3548: 3522: 3470: 3444: 3392: 3366: 3314: 3288: 3235: 3189: 3151: 3102: 3075: 3043: 3012: 2981: 2955: 2923: 2897: 2834: 2814: 2788: 2729: 2709: 2685: 2662: 2642: 2622: 2602: 2582: 2537: 2511: 2480: 2454: 2423: 2397: 2366: 2340: 2308: 2288: 2237: 2072: 2014: 1978: 1976:{\displaystyle T^{-}} 1951: 1949:{\displaystyle T^{+}} 1924: 1904: 1537: 1470: 1430: 1253: 1251:{\displaystyle T^{-}} 1223: 1221:{\displaystyle T^{+}} 1193: 1170: 1150: 1108: 1024: 956: 896: 876: 874:{\displaystyle R_{i}} 845: 825: 803: 742: 724: 697: 671: 630: 604: 562: 539: 493: 425: 352: 299: 259: 205: 14553:Probabilistic design 14138:Principal components 13981:Exponential families 13933:Nonlinear regression 13912:General linear model 13874:Mixed effects models 13864:Errors and residuals 13841:Confounding variable 13743:Bayesian probability 13721:Van der Waerden test 13711:Ordered alternative 13476:Multiple comparisons 13355:Rao–Blackwellization 13318:Estimating equations 13274:Statistical distance 12992:Factorial experiment 12525:Arithmetic-Geometric 11954:Conover, pp. 358–359 11936:Conover, pp. 352–353 11667:Conover, pp. 352–357 11220: 11200: 11162: 11080: 10999: 10965: 10939: 10915: 10644: 10616: 10593: 10572: 10517: 10483: 10449: 10428: 10224: 10203: 10148: 10114: 10080: 10059: 10018: 9954: 9934: 9907: 9880: 9860: 9828: 9796: 9769: 9739: 9683: 9565: 9434: 9333: 9306: 9286: 9266: 9221: 9201: 9181: 9161: 9061: 9041: 8991: 8964: 8839: 8650: 8330: 8303: 8276: 8256: 8236: 8184: 8062: 8019: 7999: 7959: 7916: 7882: 7789: 7762: 7729: 7685: 7665: 7645: 7601: 7581: 7554: 7516: 7394: 7345: 7319: 7270: 7237: 7188: 7146: 7119: 7081: 7041: 6998: 6971: 6951: 6924: 6904: 6881: 6854: 6828: 6802: 6775: 6755: 6735: 6687: 6639: 6590: 6540: 6520: 6500: 6480: 6427: 6413:{\displaystyle \mu } 6404: 6360: 6340: 6320: 6300: 6280: 6260: 6240: 6214: 6194: 6142: 6115: 6088: 6061: 6034: 5988: 5961: 5934: 5930:is assigned rank 1, 5907: 5729: 5688: 5645: 5608: 5570: 5550: 5495: 5440: 5414: 5389: 5369: 5351:{\displaystyle \mu } 5342: 5297: 5247: 5212: 5192: 5145: 5110: 5051: 5016: 4953: 4887: 4847: 4821: 4781: 4735: 4708: 4600: 4574: 4534: 4423: 4397: 4357: 4299: 4243: 4203: 4140: 4094: 4068: 3998: 3952: 3926: 3856: 3810: 3784: 3716: 3670: 3624: 3574: 3531: 3527:are symmetric about 3491: 3453: 3449:are symmetric about 3413: 3375: 3371:are symmetric about 3335: 3297: 3293:are symmetric about 3257: 3198: 3163: 3120: 3084: 3057: 3032: 3001: 2964: 2944: 2906: 2847: 2823: 2797: 2738: 2718: 2698: 2674: 2660:{\displaystyle \mu } 2651: 2631: 2611: 2600:{\displaystyle \mu } 2591: 2550: 2520: 2500: 2463: 2443: 2406: 2386: 2349: 2329: 2297: 2277: 2081: 2023: 1993: 1960: 1933: 1913: 1546: 1479: 1439: 1262: 1235: 1205: 1182: 1178:The signed-rank sum 1159: 1117: 1033: 965: 961:. Additionally, if 905: 885: 858: 834: 830:-value by comparing 814: 733: 713: 680: 639: 613: 575: 551: 502: 436: 365: 315: 268: 222: 130: 14625:Official statistics 14548:Methods engineering 14229:Seasonal adjustment 13997:Poisson regressions 13917:Bayesian regression 13856:Regression analysis 13836:Partial correlation 13808:Regression analysis 13407:Prediction interval 13402:Likelihood interval 13392:Confidence interval 13384:Interval estimation 13345:Unbiased estimators 13163:Model specification 13043:Up-and-down designs 12731:Partial correlation 12687:Index of dispersion 12605:Interquartile range 12365:www.stat.purdue.edu 11619:. Springer-Verlag. 11520:Biometrics Bulletin 9974: 9845: 9813: 9761:. These are called 9754:{\displaystyle n-1} 6843:{\displaystyle T=t} 6817:{\displaystyle T=t} 6705:average probability 6559:{\displaystyle |T|} 6229:{\displaystyle k-1} 2960:is symmetric about 2516:is symmetric about 2459:is symmetric about 2402:is symmetric about 2345:is symmetric about 78:alternative to the 75:normal distribution 14645:Spatial statistics 14525:Medical statistics 14425:First hitting time 14379:Whittle likelihood 14030:Degrees of freedom 14025:Multivariate ANOVA 13958:Heteroscedasticity 13770:Bayesian estimator 13735:Bayesian inference 13584:Kolmogorov–Smirnov 13469:Randomization test 13439:Testing hypotheses 13412:Tolerance interval 13323:Maximum likelihood 13218:Exponential family 13151:Density estimation 13111:Statistical theory 13071:Natural experiment 13017:Scientific control 12934:Survey methodology 12620:Standard deviation 12214:(319): 1068–1069. 11981:Pratt, pp. 661–662 11540:10338.dmlcz/135688 11226: 11206: 11183: 11147: 11065: 10978: 10947: 10921: 10663: 10629: 10601: 10578: 10555: 10502: 10468: 10434: 10232: 10209: 10186: 10133: 10099: 10065: 10031: 10004: 9960: 9940: 9920: 9893: 9866: 9846: 9831: 9814: 9799: 9782: 9751: 9718: 9662: 9660: 9551: 9420: 9319: 9292: 9272: 9252: 9207: 9187: 9167: 9145: 9047: 9024: 8977: 8950: 8867: 8825: 8634: 8632: 8316: 8289: 8262: 8242: 8219: 8170: 8048: 8005: 7985: 7945: 7907:partition function 7895: 7868: 7775: 7748: 7715: 7671: 7651: 7631: 7587: 7567: 7540: 7502: 7380: 7331: 7305: 7256: 7223: 7174: 7132: 7105: 7067: 7027: 6984: 6957: 6937: 6910: 6887: 6867: 6840: 6814: 6788: 6761: 6741: 6693: 6666: 6617: 6556: 6526: 6506: 6486: 6469:Random tiebreaking 6451: 6410: 6386: 6346: 6326: 6306: 6286: 6266: 6246: 6226: 6200: 6180: 6138:are assigned rank 6128: 6101: 6074: 6047: 6020: 5984:are assigned rank 5974: 5947: 5920: 5893: 5712: 5677:midrank procedure. 5658: 5623: 5621: 5576: 5556: 5536: 5481: 5426: 5395: 5375: 5348: 5321: 5268: 5233: 5198: 5178: 5131: 5084: 5037: 4966: 4939: 4873: 4833: 4807: 4767: 4721: 4685: 4586: 4560: 4508: 4409: 4383: 4331: 4269: 4229: 4184: 4126: 4080: 4042: 3984: 3938: 3900: 3842: 3796: 3758: 3702: 3656: 3606: 3543: 3517: 3465: 3439: 3387: 3361: 3309: 3283: 3230: 3184: 3146: 3097: 3070: 3038: 3007: 2976: 2950: 2918: 2892: 2829: 2809: 2783: 2724: 2704: 2680: 2657: 2637: 2617: 2597: 2577: 2532: 2506: 2475: 2449: 2418: 2392: 2361: 2335: 2303: 2283: 2232: 2230: 2067: 2036: 2009: 1973: 1946: 1919: 1899: 1897: 1532: 1465: 1425: 1423: 1407: 1329: 1248: 1218: 1188: 1165: 1145: 1103: 1019: 951: 891: 871: 840: 820: 798: 719: 692: 666: 625: 599: 557: 534: 488: 420: 347: 294: 264:by its difference 254: 200: 14760:Statistical tests 14747: 14746: 14685: 14684: 14681: 14680: 14620:National accounts 14590:Actuarial science 14582:Social statistics 14475: 14474: 14471: 14470: 14467: 14466: 14402:Survival function 14387: 14386: 14249:Granger causality 14090:Contingency table 14065:Survival analysis 14042: 14041: 14038: 14037: 13894:Linear regression 13789: 13788: 13785: 13784: 13760:Credible interval 13729: 13728: 13512: 13511: 13328:Method of moments 13197:Parametric family 13158:Statistical model 13088: 13087: 13084: 13083: 13002:Random assignment 12924:Statistical power 12858: 12857: 12854: 12853: 12703:Contingency table 12673: 12672: 12540:Generalized/power 12346:978-0-387-79053-4 12305:10.2466/11.IT.3.1 12065:978-1-4200-7762-9 11780:978-0-470-38737-5 11626:978-1-4612-5933-6 11209:{\displaystyle p} 11171: 11134: 11127: 10945: 10910: 10909: 10906: 10905: 10599: 10437:{\displaystyle i} 10415: 10414: 10230: 10068:{\displaystyle i} 9943:{\displaystyle F} 9869:{\displaystyle T} 9546: 9415: 9385: 9295:{\displaystyle T} 9275:{\displaystyle t} 9210:{\displaystyle z} 9190:{\displaystyle n} 9170:{\displaystyle T} 9094: 9050:{\displaystyle T} 8945: 8944: 8943: 8897: 8866: 8788: 8625: 8551: 8414: 8265:{\displaystyle T} 8245:{\displaystyle n} 8008:{\displaystyle n} 7674:{\displaystyle n} 7654:{\displaystyle n} 7590:{\displaystyle n} 6960:{\displaystyle n} 6913:{\displaystyle T} 6890:{\displaystyle T} 6764:{\displaystyle n} 6744:{\displaystyle T} 6696:{\displaystyle T} 6681:average statistic 6529:{\displaystyle T} 6509:{\displaystyle T} 6489:{\displaystyle T} 6329:{\displaystyle k} 6309:{\displaystyle v} 6289:{\displaystyle v} 6249:{\displaystyle v} 6203:{\displaystyle v} 5620: 5579:{\displaystyle j} 5559:{\displaystyle i} 4341:are exchangeable. 4295:The observations 3570:The observations 3487:The observations 3409:The observations 3331:The observations 3253:The observations 3041:{\displaystyle F} 3010:{\displaystyle F} 2953:{\displaystyle F} 2832:{\displaystyle F} 2727:{\displaystyle X} 2707:{\displaystyle F} 2683:{\displaystyle F} 2640:{\displaystyle F} 2620:{\displaystyle F} 2509:{\displaystyle F} 2452:{\displaystyle F} 2395:{\displaystyle F} 2338:{\displaystyle F} 2306:{\displaystyle F} 2286:{\displaystyle F} 2035: 1922:{\displaystyle T} 1874: 1844: 1758: 1745: 1702: 1651: 1638: 1595: 1389: 1364: 1311: 1286: 1230:negative-rank sum 1200:positive-rank sum 1191:{\displaystyle T} 1168:{\displaystyle i} 894:{\displaystyle j} 881:is the number of 843:{\displaystyle T} 823:{\displaystyle p} 722:{\displaystyle T} 14777: 14735: 14734: 14723: 14722: 14712: 14711: 14697: 14696: 14600:Crime statistics 14494: 14493: 14481: 14480: 14398: 14397: 14364:Fourier analysis 14351:Frequency domain 14331: 14278: 14244:Structural break 14204: 14203: 14153:Cluster analysis 14100:Log-linear model 14073: 14072: 14048: 14047: 13989: 13963:Homoscedasticity 13819: 13818: 13795: 13794: 13714: 13706: 13698: 13697:(Kruskal–Wallis) 13682: 13667: 13622:Cross validation 13607: 13589:Anderson–Darling 13536: 13523: 13522: 13494:Likelihood-ratio 13486:Parametric tests 13464:Permutation test 13447:1- & 2-tails 13338:Minimum distance 13310:Point estimation 13306: 13305: 13257:Optimal decision 13208: 13107: 13106: 13094: 13093: 13076:Quasi-experiment 13026:Adaptive designs 12877: 12876: 12864: 12863: 12741:Rank correlation 12503: 12502: 12494: 12493: 12481: 12480: 12448: 12441: 12434: 12425: 12424: 12375: 12374: 12372: 12371: 12357: 12351: 12350: 12330: 12324: 12323: 12317: 12309: 12307: 12287: 12278: 12275: 12269: 12266: 12260: 12257: 12251: 12248: 12242: 12239: 12233: 12230: 12224: 12223: 12203: 12197: 12194: 12188: 12185: 12179: 12178: 12176: 12152: 12143: 12140: 12134: 12131: 12125: 12122: 12116: 12113: 12107: 12104: 12098: 12095: 12089: 12086: 12080: 12077: 12071: 12069: 12051: 12045: 12042: 12036: 12033: 12027: 12024: 12018: 12015: 12009: 12006: 12000: 11997: 11991: 11988: 11982: 11979: 11973: 11970: 11964: 11961: 11955: 11952: 11946: 11943: 11937: 11934: 11928: 11925: 11919: 11918: 11909:(344): 985–988. 11898: 11892: 11891: 11879: 11873: 11870: 11864: 11861: 11855: 11854: 11845:(287): 655–667. 11834: 11828: 11827: 11819: 11813: 11810: 11804: 11801: 11795: 11792: 11786: 11784: 11767:Hollander, Myles 11763: 11757: 11754: 11748: 11745: 11739: 11736: 11730: 11727: 11721: 11718: 11712: 11709: 11703: 11700: 11694: 11692: 11674: 11668: 11665: 11659: 11656: 11650: 11647: 11641: 11638: 11632: 11630: 11612: 11606: 11603: 11597: 11594: 11588: 11585: 11579: 11578: 11558: 11552: 11551: 11517: 11508: 11502: 11501: 11499: 11498: 11484: 11478: 11476: 11458: 11418: 11407: 11385: 11369: 11368: 11365: 11362: 11359: 11356: 11353: 11350: 11347: 11344: 11341: 11235: 11233: 11232: 11227: 11215: 11213: 11212: 11207: 11192: 11190: 11189: 11184: 11182: 11181: 11172: 11169: 11156: 11154: 11153: 11148: 11140: 11139: 11135: 11132: 11125: 11095: 11087: 11074: 11072: 11071: 11066: 10987: 10985: 10984: 10979: 10977: 10976: 10956: 10954: 10953: 10948: 10946: 10943: 10930: 10928: 10927: 10922: 10672: 10670: 10669: 10664: 10662: 10661: 10638: 10636: 10635: 10630: 10628: 10627: 10610: 10608: 10607: 10602: 10600: 10597: 10587: 10585: 10584: 10579: 10564: 10562: 10561: 10556: 10554: 10553: 10535: 10534: 10511: 10509: 10508: 10503: 10501: 10500: 10477: 10475: 10474: 10469: 10467: 10466: 10443: 10441: 10440: 10435: 10422: 10421: 10241: 10239: 10238: 10233: 10231: 10228: 10218: 10216: 10215: 10210: 10195: 10193: 10192: 10187: 10185: 10184: 10166: 10165: 10142: 10140: 10139: 10134: 10132: 10131: 10108: 10106: 10105: 10100: 10098: 10097: 10074: 10072: 10071: 10066: 10053: 10052: 10049: 10040: 10038: 10037: 10032: 10030: 10029: 10013: 10011: 10010: 10005: 9979: 9973: 9968: 9949: 9947: 9946: 9941: 9929: 9927: 9926: 9921: 9919: 9918: 9902: 9900: 9899: 9894: 9892: 9891: 9875: 9873: 9872: 9867: 9855: 9853: 9852: 9847: 9844: 9839: 9823: 9821: 9820: 9815: 9812: 9807: 9791: 9789: 9788: 9783: 9781: 9780: 9760: 9758: 9757: 9752: 9727: 9725: 9724: 9719: 9714: 9713: 9701: 9700: 9671: 9669: 9668: 9663: 9661: 9654: 9649: 9648: 9629: 9628: 9603: 9602: 9560: 9558: 9557: 9552: 9547: 9542: 9538: 9451: 9446: 9445: 9429: 9427: 9426: 9421: 9416: 9411: 9391: 9386: 9381: 9361: 9353: 9352: 9340: 9328: 9326: 9325: 9320: 9318: 9317: 9301: 9299: 9298: 9293: 9281: 9279: 9278: 9273: 9261: 9259: 9258: 9253: 9242: 9241: 9216: 9214: 9213: 9208: 9196: 9194: 9193: 9188: 9176: 9174: 9173: 9168: 9154: 9152: 9151: 9146: 9138: 9137: 9115: 9110: 9095: 9093: 9092: 9080: 9056: 9054: 9053: 9048: 9033: 9031: 9030: 9025: 9020: 9019: 9015: 8986: 8984: 8983: 8978: 8976: 8975: 8959: 8957: 8956: 8951: 8946: 8939: 8901: 8900: 8899: 8898: 8893: 8873: 8868: 8859: 8849: 8834: 8832: 8831: 8826: 8809: 8808: 8796: 8795: 8789: 8787: 8746: 8730: 8729: 8716: 8714: 8713: 8668: 8667: 8643: 8641: 8640: 8635: 8633: 8626: 8621: 8583: 8552: 8547: 8509: 8501: 8500: 8472: 8471: 8427: 8415: 8410: 8390: 8382: 8381: 8369: 8354: 8353: 8341: 8325: 8323: 8322: 8317: 8315: 8314: 8298: 8296: 8295: 8290: 8288: 8287: 8271: 8269: 8268: 8263: 8251: 8249: 8248: 8243: 8228: 8226: 8225: 8220: 8215: 8214: 8202: 8201: 8179: 8177: 8176: 8171: 8160: 8159: 8147: 8146: 8125: 8124: 8112: 8111: 8090: 8089: 8077: 8076: 8057: 8055: 8054: 8049: 8044: 8043: 8031: 8030: 8014: 8012: 8011: 8006: 7994: 7992: 7991: 7986: 7984: 7983: 7971: 7970: 7954: 7952: 7951: 7946: 7941: 7940: 7928: 7927: 7904: 7902: 7901: 7896: 7894: 7893: 7877: 7875: 7874: 7869: 7867: 7866: 7857: 7849: 7848: 7836: 7835: 7820: 7819: 7807: 7806: 7784: 7782: 7781: 7776: 7774: 7773: 7757: 7755: 7754: 7749: 7741: 7740: 7724: 7722: 7721: 7716: 7680: 7678: 7677: 7672: 7660: 7658: 7657: 7652: 7640: 7638: 7637: 7632: 7596: 7594: 7593: 7588: 7576: 7574: 7573: 7568: 7566: 7565: 7549: 7547: 7546: 7541: 7511: 7509: 7508: 7503: 7489: 7488: 7476: 7475: 7454: 7453: 7441: 7440: 7419: 7418: 7406: 7405: 7389: 7387: 7386: 7381: 7376: 7340: 7338: 7337: 7332: 7314: 7312: 7311: 7306: 7295: 7294: 7282: 7281: 7265: 7263: 7262: 7257: 7249: 7248: 7232: 7230: 7229: 7224: 7213: 7212: 7200: 7199: 7183: 7181: 7180: 7175: 7158: 7157: 7141: 7139: 7138: 7133: 7131: 7130: 7114: 7112: 7111: 7106: 7076: 7074: 7073: 7068: 7066: 7065: 7053: 7052: 7036: 7034: 7033: 7028: 7023: 7022: 7010: 7009: 6993: 6991: 6990: 6985: 6983: 6982: 6966: 6964: 6963: 6958: 6946: 6944: 6943: 6938: 6936: 6935: 6919: 6917: 6916: 6911: 6896: 6894: 6893: 6888: 6876: 6874: 6873: 6868: 6866: 6865: 6849: 6847: 6846: 6841: 6823: 6821: 6820: 6815: 6797: 6795: 6794: 6789: 6787: 6786: 6770: 6768: 6767: 6762: 6750: 6748: 6747: 6742: 6702: 6700: 6699: 6694: 6675: 6673: 6672: 6667: 6665: 6664: 6655: 6626: 6624: 6623: 6618: 6616: 6615: 6606: 6565: 6563: 6562: 6557: 6555: 6547: 6535: 6533: 6532: 6527: 6515: 6513: 6512: 6507: 6495: 6493: 6492: 6487: 6460: 6458: 6457: 6452: 6419: 6417: 6416: 6411: 6395: 6393: 6392: 6387: 6382: 6355: 6353: 6352: 6347: 6335: 6333: 6332: 6327: 6315: 6313: 6312: 6307: 6295: 6293: 6292: 6287: 6275: 6273: 6272: 6267: 6255: 6253: 6252: 6247: 6235: 6233: 6232: 6227: 6209: 6207: 6206: 6201: 6189: 6187: 6186: 6181: 6170: 6137: 6135: 6134: 6129: 6127: 6126: 6110: 6108: 6107: 6102: 6100: 6099: 6083: 6081: 6080: 6075: 6073: 6072: 6056: 6054: 6053: 6048: 6046: 6045: 6029: 6027: 6026: 6021: 6010: 5983: 5981: 5980: 5975: 5973: 5972: 5956: 5954: 5953: 5948: 5946: 5945: 5929: 5927: 5926: 5921: 5919: 5918: 5902: 5900: 5899: 5894: 5889: 5884: 5883: 5874: 5866: 5861: 5860: 5851: 5843: 5838: 5837: 5828: 5820: 5815: 5814: 5805: 5797: 5792: 5791: 5782: 5774: 5769: 5768: 5759: 5751: 5746: 5745: 5736: 5721: 5719: 5718: 5713: 5667: 5665: 5664: 5659: 5657: 5656: 5632: 5630: 5629: 5624: 5622: 5613: 5585: 5583: 5582: 5577: 5565: 5563: 5562: 5557: 5545: 5543: 5542: 5537: 5526: 5525: 5513: 5512: 5490: 5488: 5487: 5482: 5471: 5470: 5458: 5457: 5435: 5433: 5432: 5427: 5404: 5402: 5401: 5396: 5384: 5382: 5381: 5376: 5357: 5355: 5354: 5349: 5330: 5328: 5327: 5322: 5277: 5275: 5274: 5269: 5267: 5266: 5257: 5242: 5240: 5239: 5234: 5232: 5231: 5222: 5207: 5205: 5204: 5199: 5187: 5185: 5184: 5179: 5171: 5170: 5161: 5140: 5138: 5137: 5132: 5130: 5129: 5120: 5093: 5091: 5090: 5085: 5077: 5076: 5067: 5046: 5044: 5043: 5038: 5036: 5035: 5026: 4975: 4973: 4972: 4967: 4965: 4964: 4948: 4946: 4945: 4940: 4938: 4937: 4925: 4924: 4912: 4911: 4899: 4898: 4882: 4880: 4879: 4874: 4872: 4871: 4859: 4858: 4842: 4840: 4839: 4834: 4816: 4814: 4813: 4808: 4806: 4805: 4793: 4792: 4776: 4774: 4773: 4768: 4763: 4762: 4750: 4749: 4730: 4728: 4727: 4722: 4720: 4719: 4694: 4692: 4691: 4686: 4675: 4674: 4662: 4661: 4634: 4633: 4621: 4620: 4595: 4593: 4592: 4587: 4569: 4567: 4566: 4561: 4559: 4558: 4546: 4545: 4530:The differences 4517: 4515: 4514: 4509: 4498: 4497: 4485: 4484: 4457: 4456: 4444: 4443: 4418: 4416: 4415: 4410: 4392: 4390: 4389: 4384: 4382: 4381: 4369: 4368: 4353:The differences 4340: 4338: 4337: 4332: 4327: 4326: 4314: 4313: 4286:Null hypothesis 4278: 4276: 4275: 4270: 4268: 4267: 4255: 4254: 4238: 4236: 4235: 4230: 4228: 4227: 4215: 4214: 4193: 4191: 4190: 4185: 4174: 4173: 4155: 4154: 4135: 4133: 4132: 4127: 4122: 4121: 4109: 4108: 4089: 4087: 4086: 4081: 4051: 4049: 4048: 4043: 4032: 4031: 4013: 4012: 3993: 3991: 3990: 3985: 3980: 3979: 3967: 3966: 3947: 3945: 3944: 3939: 3909: 3907: 3906: 3901: 3890: 3889: 3871: 3870: 3851: 3849: 3848: 3843: 3838: 3837: 3825: 3824: 3805: 3803: 3802: 3797: 3767: 3765: 3764: 3759: 3711: 3709: 3708: 3703: 3698: 3697: 3685: 3684: 3665: 3663: 3662: 3657: 3652: 3651: 3639: 3638: 3615: 3613: 3612: 3607: 3602: 3601: 3589: 3588: 3561:Null hypothesis 3552: 3550: 3549: 3544: 3526: 3524: 3523: 3518: 3516: 3515: 3503: 3502: 3474: 3472: 3471: 3466: 3448: 3446: 3445: 3440: 3438: 3437: 3425: 3424: 3396: 3394: 3393: 3388: 3370: 3368: 3367: 3362: 3360: 3359: 3347: 3346: 3318: 3316: 3315: 3310: 3292: 3290: 3289: 3284: 3282: 3281: 3269: 3268: 3244:Null hypothesis 3239: 3237: 3236: 3231: 3226: 3225: 3213: 3212: 3193: 3191: 3190: 3185: 3155: 3153: 3152: 3147: 3145: 3144: 3132: 3131: 3111:Paired data test 3106: 3104: 3103: 3098: 3096: 3095: 3079: 3077: 3076: 3071: 3069: 3068: 3047: 3045: 3044: 3039: 3016: 3014: 3013: 3008: 2985: 2983: 2982: 2977: 2959: 2957: 2956: 2951: 2932:Null hypothesis 2927: 2925: 2924: 2919: 2901: 2899: 2898: 2893: 2838: 2836: 2835: 2830: 2818: 2816: 2815: 2810: 2792: 2790: 2789: 2784: 2733: 2731: 2730: 2725: 2713: 2711: 2710: 2705: 2689: 2687: 2686: 2681: 2666: 2664: 2663: 2658: 2646: 2644: 2643: 2638: 2626: 2624: 2623: 2618: 2606: 2604: 2603: 2598: 2586: 2584: 2583: 2578: 2541: 2539: 2538: 2533: 2515: 2513: 2512: 2507: 2484: 2482: 2481: 2476: 2458: 2456: 2455: 2450: 2427: 2425: 2424: 2419: 2401: 2399: 2398: 2393: 2370: 2368: 2367: 2362: 2344: 2342: 2341: 2336: 2317:Null hypothesis 2312: 2310: 2309: 2304: 2292: 2290: 2289: 2284: 2241: 2239: 2238: 2233: 2231: 2191: 2190: 2169: 2168: 2119: 2118: 2097: 2096: 2076: 2074: 2073: 2068: 2063: 2062: 2050: 2049: 2037: 2028: 2018: 2016: 2015: 2010: 2008: 2007: 1982: 1980: 1979: 1974: 1972: 1971: 1955: 1953: 1952: 1947: 1945: 1944: 1928: 1926: 1925: 1920: 1908: 1906: 1905: 1900: 1898: 1891: 1890: 1875: 1870: 1850: 1845: 1840: 1820: 1815: 1814: 1799: 1798: 1786: 1785: 1759: 1751: 1746: 1741: 1721: 1716: 1715: 1703: 1698: 1678: 1669: 1668: 1652: 1644: 1639: 1634: 1614: 1609: 1608: 1596: 1591: 1571: 1562: 1561: 1541: 1539: 1538: 1533: 1528: 1474: 1472: 1471: 1466: 1464: 1463: 1451: 1450: 1434: 1432: 1431: 1426: 1424: 1417: 1416: 1406: 1399: 1398: 1387: 1356: 1355: 1339: 1338: 1328: 1321: 1320: 1309: 1278: 1277: 1257: 1255: 1254: 1249: 1247: 1246: 1227: 1225: 1224: 1219: 1217: 1216: 1197: 1195: 1194: 1189: 1174: 1172: 1171: 1166: 1154: 1152: 1151: 1146: 1138: 1137: 1112: 1110: 1109: 1104: 1102: 1097: 1096: 1078: 1064: 1059: 1058: 1040: 1028: 1026: 1025: 1020: 960: 958: 957: 952: 950: 945: 944: 935: 927: 922: 921: 912: 900: 898: 897: 892: 880: 878: 877: 872: 870: 869: 849: 847: 846: 841: 829: 827: 826: 821: 807: 805: 804: 799: 794: 793: 781: 780: 761: 756: 728: 726: 725: 720: 701: 699: 698: 693: 675: 673: 672: 667: 634: 632: 631: 626: 608: 606: 605: 600: 566: 564: 563: 558: 543: 541: 540: 535: 533: 532: 514: 513: 497: 495: 494: 489: 487: 482: 481: 472: 458: 453: 452: 443: 429: 427: 426: 421: 416: 411: 410: 401: 387: 382: 381: 372: 356: 354: 353: 348: 346: 345: 327: 326: 303: 301: 300: 295: 293: 292: 280: 279: 263: 261: 260: 255: 250: 249: 237: 236: 209: 207: 206: 201: 196: 195: 183: 182: 158: 157: 145: 144: 14785: 14784: 14780: 14779: 14778: 14776: 14775: 14774: 14750: 14749: 14748: 14743: 14706: 14677: 14639: 14576: 14562:quality control 14529: 14511:Clinical trials 14488: 14463: 14447: 14435:Hazard function 14429: 14383: 14345: 14329: 14292: 14288:Breusch–Godfrey 14276: 14253: 14193: 14168:Factor analysis 14114: 14095:Graphical model 14067: 14034: 14001: 13987: 13967: 13921: 13888: 13850: 13813: 13812: 13781: 13725: 13712: 13704: 13696: 13680: 13665: 13644:Rank statistics 13638: 13617:Model selection 13605: 13563:Goodness of fit 13557: 13534: 13508: 13480: 13433: 13378: 13367:Median unbiased 13295: 13206: 13139:Order statistic 13101: 13080: 13047: 13021: 12973: 12928: 12871: 12869:Data collection 12850: 12762: 12717: 12691: 12669: 12629: 12581: 12498:Continuous data 12488: 12475: 12457: 12452: 12419:link to article 12384: 12379: 12378: 12369: 12367: 12359: 12358: 12354: 12347: 12331: 12327: 12311: 12310: 12288: 12281: 12276: 12272: 12267: 12263: 12258: 12254: 12249: 12245: 12241:Wilcoxon, p. 82 12240: 12236: 12231: 12227: 12204: 12200: 12195: 12191: 12186: 12182: 12153: 12146: 12141: 12137: 12132: 12128: 12123: 12119: 12114: 12110: 12105: 12101: 12096: 12092: 12087: 12083: 12078: 12074: 12066: 12052: 12048: 12043: 12039: 12034: 12030: 12025: 12021: 12016: 12012: 12007: 12003: 11998: 11994: 11989: 11985: 11980: 11976: 11971: 11967: 11962: 11958: 11953: 11949: 11944: 11940: 11935: 11931: 11926: 11922: 11899: 11895: 11880: 11876: 11871: 11867: 11862: 11858: 11835: 11831: 11820: 11816: 11811: 11807: 11802: 11798: 11793: 11789: 11781: 11764: 11760: 11756:Conover, p. 354 11755: 11751: 11746: 11742: 11737: 11733: 11728: 11724: 11720:Conover, p. 353 11719: 11715: 11710: 11706: 11701: 11697: 11689: 11675: 11671: 11666: 11662: 11657: 11653: 11648: 11644: 11639: 11635: 11627: 11613: 11609: 11605:Conover, p. 353 11604: 11600: 11595: 11591: 11587:Conover, p. 352 11586: 11582: 11575: 11559: 11555: 11532:10.2307/3001968 11515: 11509: 11505: 11496: 11494: 11486: 11485: 11481: 11473: 11459: 11455: 11450: 11433: 11406:= signrank(x,y) 11383: 11366: 11363: 11360: 11357: 11354: 11351: 11348: 11345: 11342: 11339: 11331: 11248: 11242: 11221: 11218: 11217: 11201: 11198: 11197: 11177: 11173: 11168: 11163: 11160: 11159: 11131: 11103: 11099: 11091: 11083: 11081: 11078: 11077: 11000: 10997: 10996: 10972: 10968: 10966: 10963: 10962: 10942: 10940: 10937: 10936: 10916: 10913: 10912: 10657: 10653: 10645: 10642: 10641: 10623: 10619: 10617: 10614: 10613: 10596: 10594: 10591: 10590: 10573: 10570: 10569: 10543: 10539: 10524: 10520: 10518: 10515: 10514: 10490: 10486: 10484: 10481: 10480: 10456: 10452: 10450: 10447: 10446: 10429: 10426: 10425: 10227: 10225: 10222: 10221: 10204: 10201: 10200: 10174: 10170: 10155: 10151: 10149: 10146: 10145: 10121: 10117: 10115: 10112: 10111: 10087: 10083: 10081: 10078: 10077: 10060: 10057: 10056: 10047: 10025: 10021: 10019: 10016: 10015: 9975: 9969: 9964: 9955: 9952: 9951: 9935: 9932: 9931: 9914: 9910: 9908: 9905: 9904: 9887: 9883: 9881: 9878: 9877: 9861: 9858: 9857: 9840: 9835: 9829: 9826: 9825: 9808: 9803: 9797: 9794: 9793: 9776: 9772: 9770: 9767: 9766: 9740: 9737: 9736: 9709: 9705: 9696: 9692: 9684: 9681: 9680: 9677: 9659: 9658: 9650: 9644: 9640: 9633: 9624: 9620: 9608: 9607: 9598: 9594: 9587: 9568: 9566: 9563: 9562: 9534: 9452: 9450: 9441: 9437: 9435: 9432: 9431: 9392: 9390: 9362: 9360: 9348: 9344: 9336: 9334: 9331: 9330: 9313: 9309: 9307: 9304: 9303: 9287: 9284: 9283: 9267: 9264: 9263: 9237: 9233: 9222: 9219: 9218: 9202: 9199: 9198: 9182: 9179: 9178: 9162: 9159: 9158: 9130: 9126: 9111: 9100: 9088: 9084: 9079: 9062: 9059: 9058: 9042: 9039: 9038: 9011: 9004: 9000: 8992: 8989: 8988: 8971: 8967: 8965: 8962: 8961: 8902: 8874: 8872: 8857: 8850: 8848: 8840: 8837: 8836: 8804: 8800: 8791: 8790: 8747: 8725: 8721: 8717: 8715: 8709: 8708: 8663: 8659: 8651: 8648: 8647: 8631: 8630: 8584: 8582: 8575: 8557: 8556: 8510: 8508: 8496: 8492: 8476: 8467: 8463: 8451: 8450: 8437: 8423: 8420: 8419: 8391: 8389: 8377: 8373: 8365: 8358: 8349: 8345: 8337: 8333: 8331: 8328: 8327: 8310: 8306: 8304: 8301: 8300: 8283: 8279: 8277: 8274: 8273: 8257: 8254: 8253: 8237: 8234: 8233: 8232:For very large 8210: 8206: 8197: 8193: 8185: 8182: 8181: 8155: 8151: 8136: 8132: 8120: 8116: 8101: 8097: 8085: 8081: 8072: 8068: 8063: 8060: 8059: 8039: 8035: 8026: 8022: 8020: 8017: 8016: 8000: 7997: 7996: 7979: 7975: 7966: 7962: 7960: 7957: 7956: 7936: 7932: 7923: 7919: 7917: 7914: 7913: 7889: 7885: 7883: 7880: 7879: 7878:. The function 7862: 7858: 7853: 7844: 7840: 7831: 7827: 7815: 7811: 7802: 7798: 7790: 7787: 7786: 7769: 7765: 7763: 7760: 7759: 7736: 7732: 7730: 7727: 7726: 7686: 7683: 7682: 7666: 7663: 7662: 7646: 7643: 7642: 7602: 7599: 7598: 7582: 7579: 7578: 7561: 7557: 7555: 7552: 7551: 7517: 7514: 7513: 7484: 7480: 7465: 7461: 7449: 7445: 7430: 7426: 7414: 7410: 7401: 7397: 7395: 7392: 7391: 7372: 7346: 7343: 7342: 7320: 7317: 7316: 7290: 7286: 7277: 7273: 7271: 7268: 7267: 7244: 7240: 7238: 7235: 7234: 7208: 7204: 7195: 7191: 7189: 7186: 7185: 7153: 7149: 7147: 7144: 7143: 7126: 7122: 7120: 7117: 7116: 7082: 7079: 7078: 7061: 7057: 7048: 7044: 7042: 7039: 7038: 7018: 7014: 7005: 7001: 6999: 6996: 6995: 6978: 6974: 6972: 6969: 6968: 6952: 6949: 6948: 6931: 6927: 6925: 6922: 6921: 6905: 6902: 6901: 6882: 6879: 6878: 6861: 6857: 6855: 6852: 6851: 6829: 6826: 6825: 6803: 6800: 6799: 6782: 6778: 6776: 6773: 6772: 6756: 6753: 6752: 6736: 6733: 6732: 6725: 6688: 6685: 6684: 6660: 6656: 6651: 6640: 6637: 6636: 6611: 6607: 6602: 6591: 6588: 6587: 6551: 6543: 6541: 6538: 6537: 6521: 6518: 6517: 6501: 6498: 6497: 6481: 6478: 6477: 6428: 6425: 6424: 6405: 6402: 6401: 6378: 6361: 6358: 6357: 6341: 6338: 6337: 6321: 6318: 6317: 6301: 6298: 6297: 6281: 6278: 6277: 6261: 6258: 6257: 6241: 6238: 6237: 6215: 6212: 6211: 6195: 6192: 6191: 6166: 6143: 6140: 6139: 6122: 6118: 6116: 6113: 6112: 6095: 6091: 6089: 6086: 6085: 6068: 6064: 6062: 6059: 6058: 6041: 6037: 6035: 6032: 6031: 6006: 5989: 5986: 5985: 5968: 5964: 5962: 5959: 5958: 5941: 5937: 5935: 5932: 5931: 5914: 5910: 5908: 5905: 5904: 5885: 5879: 5875: 5870: 5862: 5856: 5852: 5847: 5839: 5833: 5829: 5824: 5816: 5810: 5806: 5801: 5793: 5787: 5783: 5778: 5770: 5764: 5760: 5755: 5747: 5741: 5737: 5732: 5730: 5727: 5726: 5689: 5686: 5685: 5652: 5648: 5646: 5643: 5642: 5639: 5611: 5609: 5606: 5605: 5571: 5568: 5567: 5551: 5548: 5547: 5521: 5517: 5508: 5504: 5496: 5493: 5492: 5466: 5462: 5453: 5449: 5441: 5438: 5437: 5415: 5412: 5411: 5390: 5387: 5386: 5370: 5367: 5366: 5343: 5340: 5339: 5298: 5295: 5294: 5262: 5258: 5253: 5248: 5245: 5244: 5227: 5223: 5218: 5213: 5210: 5209: 5193: 5190: 5189: 5166: 5162: 5157: 5146: 5143: 5142: 5125: 5121: 5116: 5111: 5108: 5107: 5072: 5068: 5063: 5052: 5049: 5048: 5031: 5027: 5022: 5017: 5014: 5013: 4982: 4960: 4956: 4954: 4951: 4950: 4933: 4929: 4920: 4916: 4907: 4903: 4894: 4890: 4888: 4885: 4884: 4867: 4863: 4854: 4850: 4848: 4845: 4844: 4822: 4819: 4818: 4801: 4797: 4788: 4784: 4782: 4779: 4778: 4758: 4754: 4745: 4741: 4736: 4733: 4732: 4715: 4711: 4709: 4706: 4705: 4702: 4670: 4666: 4657: 4653: 4629: 4625: 4616: 4612: 4601: 4598: 4597: 4575: 4572: 4571: 4554: 4550: 4541: 4537: 4535: 4532: 4531: 4527: 4493: 4489: 4480: 4476: 4452: 4448: 4439: 4435: 4424: 4421: 4420: 4398: 4395: 4394: 4377: 4373: 4364: 4360: 4358: 4355: 4354: 4350: 4322: 4318: 4309: 4305: 4300: 4297: 4296: 4292: 4263: 4259: 4250: 4246: 4244: 4241: 4240: 4223: 4219: 4210: 4206: 4204: 4201: 4200: 4169: 4165: 4150: 4146: 4141: 4138: 4137: 4117: 4113: 4104: 4100: 4095: 4092: 4091: 4069: 4066: 4065: 4061: 4027: 4023: 4008: 4004: 3999: 3996: 3995: 3975: 3971: 3962: 3958: 3953: 3950: 3949: 3927: 3924: 3923: 3919: 3885: 3881: 3866: 3862: 3857: 3854: 3853: 3833: 3829: 3820: 3816: 3811: 3808: 3807: 3785: 3782: 3781: 3777: 3717: 3714: 3713: 3693: 3689: 3680: 3676: 3671: 3668: 3667: 3647: 3643: 3634: 3630: 3625: 3622: 3621: 3620:, meaning that 3597: 3593: 3584: 3580: 3575: 3572: 3571: 3567: 3532: 3529: 3528: 3511: 3507: 3498: 3494: 3492: 3489: 3488: 3484: 3454: 3451: 3450: 3433: 3429: 3420: 3416: 3414: 3411: 3410: 3406: 3376: 3373: 3372: 3355: 3351: 3342: 3338: 3336: 3333: 3332: 3328: 3298: 3295: 3294: 3277: 3273: 3264: 3260: 3258: 3255: 3254: 3250: 3221: 3217: 3208: 3204: 3199: 3196: 3195: 3164: 3161: 3160: 3140: 3136: 3127: 3123: 3121: 3118: 3117: 3113: 3091: 3087: 3085: 3082: 3081: 3064: 3060: 3058: 3055: 3054: 3033: 3030: 3029: 3026: 3002: 2999: 2998: 2995: 2965: 2962: 2961: 2945: 2942: 2941: 2938: 2907: 2904: 2903: 2848: 2845: 2844: 2824: 2821: 2820: 2798: 2795: 2794: 2739: 2736: 2735: 2719: 2716: 2715: 2699: 2696: 2695: 2675: 2672: 2671: 2652: 2649: 2648: 2632: 2629: 2628: 2612: 2609: 2608: 2607:is a median of 2592: 2589: 2588: 2551: 2548: 2547: 2546:If in addition 2521: 2518: 2517: 2501: 2498: 2497: 2494: 2464: 2461: 2460: 2444: 2441: 2440: 2437: 2407: 2404: 2403: 2387: 2384: 2383: 2380: 2350: 2347: 2346: 2330: 2327: 2326: 2323: 2298: 2295: 2294: 2278: 2275: 2274: 2252: 2250:One-sample test 2247: 2229: 2228: 2183: 2179: 2164: 2160: 2157: 2156: 2111: 2107: 2092: 2088: 2084: 2082: 2079: 2078: 2058: 2054: 2045: 2041: 2026: 2024: 2021: 2020: 2000: 1996: 1994: 1991: 1990: 1967: 1963: 1961: 1958: 1957: 1940: 1936: 1934: 1931: 1930: 1914: 1911: 1910: 1896: 1895: 1886: 1882: 1851: 1849: 1821: 1819: 1810: 1806: 1794: 1790: 1781: 1777: 1770: 1764: 1763: 1750: 1722: 1720: 1711: 1707: 1679: 1677: 1670: 1664: 1660: 1657: 1656: 1643: 1615: 1613: 1604: 1600: 1572: 1570: 1563: 1557: 1553: 1549: 1547: 1544: 1543: 1524: 1480: 1477: 1476: 1459: 1455: 1446: 1442: 1440: 1437: 1436: 1422: 1421: 1412: 1408: 1394: 1390: 1368: 1357: 1351: 1347: 1344: 1343: 1334: 1330: 1316: 1312: 1290: 1279: 1273: 1269: 1265: 1263: 1260: 1259: 1258:are defined by 1242: 1238: 1236: 1233: 1232: 1212: 1208: 1206: 1203: 1202: 1183: 1180: 1179: 1160: 1157: 1156: 1124: 1120: 1118: 1115: 1114: 1098: 1083: 1079: 1074: 1060: 1045: 1041: 1036: 1034: 1031: 1030: 966: 963: 962: 946: 940: 936: 931: 923: 917: 913: 908: 906: 903: 902: 886: 883: 882: 865: 861: 859: 856: 855: 835: 832: 831: 815: 812: 811: 789: 785: 776: 772: 757: 746: 734: 731: 730: 714: 711: 710: 708:signed-rank sum 681: 678: 677: 640: 637: 636: 614: 611: 610: 576: 573: 572: 552: 549: 548: 528: 524: 509: 505: 503: 500: 499: 483: 477: 473: 468: 454: 448: 444: 439: 437: 434: 433: 412: 406: 402: 397: 383: 377: 373: 368: 366: 363: 362: 341: 337: 322: 318: 316: 313: 312: 288: 284: 275: 271: 269: 266: 265: 245: 241: 232: 228: 223: 220: 219: 191: 187: 178: 174: 153: 149: 140: 136: 131: 128: 127: 120: 88: 24: 17: 12: 11: 5: 14783: 14773: 14772: 14767: 14762: 14745: 14744: 14742: 14741: 14729: 14717: 14703: 14690: 14687: 14686: 14683: 14682: 14679: 14678: 14676: 14675: 14670: 14665: 14660: 14655: 14649: 14647: 14641: 14640: 14638: 14637: 14632: 14627: 14622: 14617: 14612: 14607: 14602: 14597: 14592: 14586: 14584: 14578: 14577: 14575: 14574: 14569: 14564: 14555: 14550: 14545: 14539: 14537: 14531: 14530: 14528: 14527: 14522: 14517: 14508: 14506:Bioinformatics 14502: 14500: 14490: 14489: 14477: 14476: 14473: 14472: 14469: 14468: 14465: 14464: 14462: 14461: 14455: 14453: 14449: 14448: 14446: 14445: 14439: 14437: 14431: 14430: 14428: 14427: 14422: 14417: 14412: 14406: 14404: 14395: 14389: 14388: 14385: 14384: 14382: 14381: 14376: 14371: 14366: 14361: 14355: 14353: 14347: 14346: 14344: 14343: 14338: 14333: 14325: 14320: 14315: 14314: 14313: 14311:partial (PACF) 14302: 14300: 14294: 14293: 14291: 14290: 14285: 14280: 14272: 14267: 14261: 14259: 14258:Specific tests 14255: 14254: 14252: 14251: 14246: 14241: 14236: 14231: 14226: 14221: 14216: 14210: 14208: 14201: 14195: 14194: 14192: 14191: 14190: 14189: 14188: 14187: 14172: 14171: 14170: 14160: 14158:Classification 14155: 14150: 14145: 14140: 14135: 14130: 14124: 14122: 14116: 14115: 14113: 14112: 14107: 14105:McNemar's test 14102: 14097: 14092: 14087: 14081: 14079: 14069: 14068: 14044: 14043: 14040: 14039: 14036: 14035: 14033: 14032: 14027: 14022: 14017: 14011: 14009: 14003: 14002: 14000: 13999: 13983: 13977: 13975: 13969: 13968: 13966: 13965: 13960: 13955: 13950: 13945: 13943:Semiparametric 13940: 13935: 13929: 13927: 13923: 13922: 13920: 13919: 13914: 13909: 13904: 13898: 13896: 13890: 13889: 13887: 13886: 13881: 13876: 13871: 13866: 13860: 13858: 13852: 13851: 13849: 13848: 13843: 13838: 13833: 13827: 13825: 13815: 13814: 13811: 13810: 13805: 13799: 13791: 13790: 13787: 13786: 13783: 13782: 13780: 13779: 13778: 13777: 13767: 13762: 13757: 13756: 13755: 13750: 13739: 13737: 13731: 13730: 13727: 13726: 13724: 13723: 13718: 13717: 13716: 13708: 13700: 13684: 13681:(Mann–Whitney) 13676: 13675: 13674: 13661: 13660: 13659: 13648: 13646: 13640: 13639: 13637: 13636: 13635: 13634: 13629: 13624: 13614: 13609: 13606:(Shapiro–Wilk) 13601: 13596: 13591: 13586: 13581: 13573: 13567: 13565: 13559: 13558: 13556: 13555: 13547: 13538: 13526: 13520: 13518:Specific tests 13514: 13513: 13510: 13509: 13507: 13506: 13501: 13496: 13490: 13488: 13482: 13481: 13479: 13478: 13473: 13472: 13471: 13461: 13460: 13459: 13449: 13443: 13441: 13435: 13434: 13432: 13431: 13430: 13429: 13424: 13414: 13409: 13404: 13399: 13394: 13388: 13386: 13380: 13379: 13377: 13376: 13371: 13370: 13369: 13364: 13363: 13362: 13357: 13342: 13341: 13340: 13335: 13330: 13325: 13314: 13312: 13303: 13297: 13296: 13294: 13293: 13288: 13283: 13282: 13281: 13271: 13266: 13265: 13264: 13254: 13253: 13252: 13247: 13242: 13232: 13227: 13222: 13221: 13220: 13215: 13210: 13194: 13193: 13192: 13187: 13182: 13172: 13171: 13170: 13165: 13155: 13154: 13153: 13143: 13142: 13141: 13131: 13126: 13121: 13115: 13113: 13103: 13102: 13090: 13089: 13086: 13085: 13082: 13081: 13079: 13078: 13073: 13068: 13063: 13057: 13055: 13049: 13048: 13046: 13045: 13040: 13035: 13029: 13027: 13023: 13022: 13020: 13019: 13014: 13009: 13004: 12999: 12994: 12989: 12983: 12981: 12975: 12974: 12972: 12971: 12969:Standard error 12966: 12961: 12956: 12955: 12954: 12949: 12938: 12936: 12930: 12929: 12927: 12926: 12921: 12916: 12911: 12906: 12901: 12899:Optimal design 12896: 12891: 12885: 12883: 12873: 12872: 12860: 12859: 12856: 12855: 12852: 12851: 12849: 12848: 12843: 12838: 12833: 12828: 12823: 12818: 12813: 12808: 12803: 12798: 12793: 12788: 12783: 12778: 12772: 12770: 12764: 12763: 12761: 12760: 12755: 12754: 12753: 12748: 12738: 12733: 12727: 12725: 12719: 12718: 12716: 12715: 12710: 12705: 12699: 12697: 12696:Summary tables 12693: 12692: 12690: 12689: 12683: 12681: 12675: 12674: 12671: 12670: 12668: 12667: 12666: 12665: 12660: 12655: 12645: 12639: 12637: 12631: 12630: 12628: 12627: 12622: 12617: 12612: 12607: 12602: 12597: 12591: 12589: 12583: 12582: 12580: 12579: 12574: 12569: 12568: 12567: 12562: 12557: 12552: 12547: 12542: 12537: 12532: 12530:Contraharmonic 12527: 12522: 12511: 12509: 12500: 12490: 12489: 12477: 12476: 12474: 12473: 12468: 12462: 12459: 12458: 12451: 12450: 12443: 12436: 12428: 12422: 12421: 12411: 12405: 12400: 12395: 12390: 12383: 12382:External links 12380: 12377: 12376: 12352: 12345: 12325: 12279: 12270: 12261: 12252: 12243: 12234: 12225: 12198: 12189: 12180: 12167:(2): 169–171. 12144: 12135: 12126: 12117: 12108: 12099: 12090: 12081: 12072: 12064: 12046: 12037: 12028: 12019: 12010: 12001: 11992: 11983: 11974: 11965: 11956: 11947: 11938: 11929: 11920: 11893: 11874: 11865: 11856: 11829: 11814: 11805: 11796: 11787: 11779: 11758: 11749: 11740: 11731: 11722: 11713: 11704: 11695: 11687: 11669: 11660: 11651: 11642: 11633: 11625: 11607: 11598: 11589: 11580: 11573: 11553: 11503: 11479: 11471: 11452: 11451: 11449: 11446: 11445: 11444: 11439: 11432: 11429: 11428: 11427: 11420: 11410: 11399: 11393: 11387: 11377: 11371: 11330: 11327: 11250:To compute an 11244:Main article: 11241: 11238: 11237: 11236: 11225: 11205: 11194: 11180: 11176: 11167: 11157: 11146: 11143: 11138: 11130: 11124: 11121: 11118: 11115: 11112: 11109: 11106: 11102: 11098: 11094: 11090: 11086: 11075: 11064: 11061: 11058: 11055: 11052: 11049: 11046: 11043: 11040: 11037: 11034: 11031: 11028: 11025: 11022: 11019: 11016: 11013: 11010: 11007: 11004: 10975: 10971: 10959:absolute value 10920: 10908: 10907: 10904: 10903: 10900: 10897: 10894: 10891: 10888: 10885: 10881: 10880: 10877: 10874: 10871: 10868: 10865: 10862: 10858: 10857: 10854: 10851: 10848: 10845: 10842: 10839: 10835: 10834: 10831: 10828: 10825: 10822: 10819: 10816: 10812: 10811: 10808: 10805: 10802: 10799: 10796: 10793: 10789: 10788: 10785: 10782: 10779: 10776: 10773: 10770: 10766: 10765: 10762: 10759: 10756: 10753: 10750: 10747: 10743: 10742: 10739: 10736: 10733: 10730: 10727: 10724: 10720: 10719: 10716: 10713: 10710: 10707: 10704: 10701: 10697: 10696: 10693: 10690: 10687: 10684: 10681: 10678: 10674: 10673: 10660: 10656: 10652: 10649: 10639: 10626: 10622: 10611: 10588: 10577: 10566: 10565: 10552: 10549: 10546: 10542: 10538: 10533: 10530: 10527: 10523: 10512: 10499: 10496: 10493: 10489: 10478: 10465: 10462: 10459: 10455: 10444: 10433: 10419: 10416: 10413: 10412: 10409: 10406: 10403: 10400: 10396: 10395: 10392: 10389: 10386: 10383: 10379: 10378: 10375: 10372: 10369: 10366: 10362: 10361: 10358: 10355: 10352: 10349: 10345: 10344: 10341: 10338: 10335: 10332: 10328: 10327: 10324: 10321: 10318: 10315: 10311: 10310: 10307: 10304: 10301: 10298: 10294: 10293: 10290: 10287: 10284: 10281: 10277: 10276: 10273: 10270: 10267: 10264: 10260: 10259: 10256: 10253: 10250: 10247: 10243: 10242: 10219: 10208: 10197: 10196: 10183: 10180: 10177: 10173: 10169: 10164: 10161: 10158: 10154: 10143: 10130: 10127: 10124: 10120: 10109: 10096: 10093: 10090: 10086: 10075: 10064: 10046: 10043: 10028: 10024: 10003: 10000: 9997: 9994: 9991: 9988: 9985: 9982: 9978: 9972: 9967: 9963: 9959: 9939: 9917: 9913: 9890: 9886: 9865: 9843: 9838: 9834: 9811: 9806: 9802: 9779: 9775: 9763:modified ranks 9750: 9747: 9744: 9717: 9712: 9708: 9704: 9699: 9695: 9691: 9688: 9676: 9673: 9657: 9653: 9647: 9643: 9639: 9636: 9634: 9632: 9627: 9623: 9619: 9616: 9613: 9610: 9609: 9606: 9601: 9597: 9593: 9590: 9588: 9586: 9583: 9580: 9577: 9574: 9571: 9570: 9550: 9545: 9541: 9537: 9533: 9530: 9527: 9524: 9521: 9518: 9515: 9512: 9509: 9506: 9503: 9500: 9497: 9494: 9491: 9488: 9485: 9482: 9479: 9476: 9473: 9470: 9467: 9464: 9461: 9458: 9455: 9449: 9444: 9440: 9419: 9414: 9410: 9407: 9404: 9401: 9398: 9395: 9389: 9384: 9380: 9377: 9374: 9371: 9368: 9365: 9359: 9356: 9351: 9347: 9343: 9339: 9316: 9312: 9291: 9271: 9251: 9248: 9245: 9240: 9236: 9232: 9229: 9226: 9206: 9186: 9166: 9144: 9141: 9136: 9133: 9129: 9125: 9122: 9119: 9114: 9109: 9106: 9103: 9099: 9091: 9087: 9083: 9078: 9075: 9072: 9069: 9066: 9046: 9023: 9018: 9014: 9010: 9007: 9003: 8999: 8996: 8974: 8970: 8949: 8942: 8938: 8935: 8932: 8929: 8926: 8923: 8920: 8917: 8914: 8911: 8908: 8905: 8896: 8892: 8889: 8886: 8883: 8880: 8877: 8871: 8865: 8862: 8856: 8853: 8847: 8844: 8824: 8821: 8818: 8815: 8812: 8807: 8803: 8799: 8794: 8786: 8783: 8780: 8777: 8774: 8771: 8768: 8765: 8762: 8759: 8756: 8753: 8750: 8745: 8742: 8739: 8736: 8733: 8728: 8724: 8720: 8712: 8707: 8704: 8701: 8698: 8695: 8692: 8689: 8686: 8683: 8680: 8677: 8674: 8671: 8666: 8662: 8658: 8655: 8629: 8624: 8620: 8617: 8614: 8611: 8608: 8605: 8602: 8599: 8596: 8593: 8590: 8587: 8581: 8578: 8576: 8574: 8571: 8568: 8565: 8562: 8559: 8558: 8555: 8550: 8546: 8543: 8540: 8537: 8534: 8531: 8528: 8525: 8522: 8519: 8516: 8513: 8507: 8504: 8499: 8495: 8491: 8488: 8485: 8482: 8479: 8477: 8475: 8470: 8466: 8462: 8459: 8456: 8453: 8452: 8449: 8446: 8443: 8440: 8438: 8436: 8433: 8430: 8426: 8422: 8421: 8418: 8413: 8409: 8406: 8403: 8400: 8397: 8394: 8388: 8385: 8380: 8376: 8372: 8368: 8364: 8361: 8359: 8357: 8352: 8348: 8344: 8340: 8336: 8335: 8313: 8309: 8286: 8282: 8261: 8241: 8218: 8213: 8209: 8205: 8200: 8196: 8192: 8189: 8169: 8166: 8163: 8158: 8154: 8150: 8145: 8142: 8139: 8135: 8131: 8128: 8123: 8119: 8115: 8110: 8107: 8104: 8100: 8096: 8093: 8088: 8084: 8080: 8075: 8071: 8067: 8047: 8042: 8038: 8034: 8029: 8025: 8004: 7982: 7978: 7974: 7969: 7965: 7944: 7939: 7935: 7931: 7926: 7922: 7892: 7888: 7865: 7861: 7856: 7852: 7847: 7843: 7839: 7834: 7830: 7826: 7823: 7818: 7814: 7810: 7805: 7801: 7797: 7794: 7772: 7768: 7747: 7744: 7739: 7735: 7725:which sums to 7714: 7711: 7708: 7705: 7702: 7699: 7696: 7693: 7690: 7670: 7650: 7630: 7627: 7624: 7621: 7618: 7615: 7612: 7609: 7606: 7586: 7564: 7560: 7550:which sums to 7539: 7536: 7533: 7530: 7527: 7524: 7521: 7501: 7498: 7495: 7492: 7487: 7483: 7479: 7474: 7471: 7468: 7464: 7460: 7457: 7452: 7448: 7444: 7439: 7436: 7433: 7429: 7425: 7422: 7417: 7413: 7409: 7404: 7400: 7379: 7375: 7371: 7368: 7365: 7362: 7359: 7356: 7353: 7350: 7330: 7327: 7324: 7304: 7301: 7298: 7293: 7289: 7285: 7280: 7276: 7255: 7252: 7247: 7243: 7222: 7219: 7216: 7211: 7207: 7203: 7198: 7194: 7173: 7170: 7167: 7164: 7161: 7156: 7152: 7129: 7125: 7104: 7101: 7098: 7095: 7092: 7089: 7086: 7064: 7060: 7056: 7051: 7047: 7026: 7021: 7017: 7013: 7008: 7004: 6981: 6977: 6956: 6934: 6930: 6909: 6886: 6864: 6860: 6839: 6836: 6833: 6813: 6810: 6807: 6785: 6781: 6760: 6740: 6724: 6721: 6692: 6663: 6659: 6654: 6650: 6647: 6644: 6633: 6632: 6614: 6610: 6605: 6601: 6598: 6595: 6584: 6583: 6576: 6575: 6554: 6550: 6546: 6525: 6505: 6485: 6450: 6447: 6444: 6441: 6438: 6435: 6432: 6409: 6385: 6381: 6377: 6374: 6371: 6368: 6365: 6345: 6325: 6305: 6285: 6265: 6245: 6225: 6222: 6219: 6199: 6179: 6176: 6173: 6169: 6165: 6162: 6159: 6156: 6153: 6150: 6147: 6125: 6121: 6098: 6094: 6071: 6067: 6044: 6040: 6019: 6016: 6013: 6009: 6005: 6002: 5999: 5996: 5993: 5971: 5967: 5944: 5940: 5917: 5913: 5903:In this case, 5892: 5888: 5882: 5878: 5873: 5869: 5865: 5859: 5855: 5850: 5846: 5842: 5836: 5832: 5827: 5823: 5819: 5813: 5809: 5804: 5800: 5796: 5790: 5786: 5781: 5777: 5773: 5767: 5763: 5758: 5754: 5750: 5744: 5740: 5735: 5711: 5708: 5705: 5702: 5699: 5696: 5693: 5655: 5651: 5638: 5635: 5619: 5616: 5575: 5555: 5535: 5532: 5529: 5524: 5520: 5516: 5511: 5507: 5503: 5500: 5480: 5477: 5474: 5469: 5465: 5461: 5456: 5452: 5448: 5445: 5425: 5422: 5419: 5407: 5406: 5394: 5374: 5363: 5359: 5347: 5336: 5320: 5317: 5314: 5311: 5308: 5305: 5302: 5265: 5261: 5256: 5252: 5230: 5226: 5221: 5217: 5197: 5177: 5174: 5169: 5165: 5160: 5156: 5153: 5150: 5128: 5124: 5119: 5115: 5100: 5099: 5083: 5080: 5075: 5071: 5066: 5062: 5059: 5056: 5034: 5030: 5025: 5021: 5006: 5005: 4998: 4997: 4981: 4978: 4963: 4959: 4936: 4932: 4928: 4923: 4919: 4915: 4910: 4906: 4902: 4897: 4893: 4870: 4866: 4862: 4857: 4853: 4832: 4829: 4826: 4804: 4800: 4796: 4791: 4787: 4766: 4761: 4757: 4753: 4748: 4744: 4740: 4718: 4714: 4701: 4700:Zeros and ties 4698: 4697: 4696: 4684: 4681: 4678: 4673: 4669: 4665: 4660: 4656: 4652: 4649: 4646: 4643: 4640: 4637: 4632: 4628: 4624: 4619: 4615: 4611: 4608: 4605: 4585: 4582: 4579: 4557: 4553: 4549: 4544: 4540: 4528: 4525: 4519: 4507: 4504: 4501: 4496: 4492: 4488: 4483: 4479: 4475: 4472: 4469: 4466: 4463: 4460: 4455: 4451: 4447: 4442: 4438: 4434: 4431: 4428: 4408: 4405: 4402: 4380: 4376: 4372: 4367: 4363: 4351: 4348: 4342: 4330: 4325: 4321: 4317: 4312: 4308: 4304: 4293: 4290: 4266: 4262: 4258: 4253: 4249: 4226: 4222: 4218: 4213: 4209: 4196: 4195: 4183: 4180: 4177: 4172: 4168: 4164: 4161: 4158: 4153: 4149: 4145: 4125: 4120: 4116: 4112: 4107: 4103: 4099: 4079: 4076: 4073: 4062: 4059: 4053: 4041: 4038: 4035: 4030: 4026: 4022: 4019: 4016: 4011: 4007: 4003: 3983: 3978: 3974: 3970: 3965: 3961: 3957: 3937: 3934: 3931: 3920: 3917: 3911: 3899: 3896: 3893: 3888: 3884: 3880: 3877: 3874: 3869: 3865: 3861: 3841: 3836: 3832: 3828: 3823: 3819: 3815: 3795: 3792: 3789: 3778: 3775: 3769: 3757: 3754: 3751: 3748: 3745: 3742: 3739: 3736: 3733: 3730: 3727: 3724: 3721: 3701: 3696: 3692: 3688: 3683: 3679: 3675: 3655: 3650: 3646: 3642: 3637: 3633: 3629: 3605: 3600: 3596: 3592: 3587: 3583: 3579: 3568: 3565: 3555: 3554: 3542: 3539: 3536: 3514: 3510: 3506: 3501: 3497: 3485: 3482: 3476: 3464: 3461: 3458: 3436: 3432: 3428: 3423: 3419: 3407: 3404: 3398: 3386: 3383: 3380: 3358: 3354: 3350: 3345: 3341: 3329: 3326: 3320: 3308: 3305: 3302: 3280: 3276: 3272: 3267: 3263: 3251: 3248: 3229: 3224: 3220: 3216: 3211: 3207: 3203: 3183: 3180: 3177: 3174: 3171: 3168: 3143: 3139: 3135: 3130: 3126: 3112: 3109: 3094: 3090: 3067: 3063: 3050: 3049: 3037: 3027: 3024: 3018: 3006: 2996: 2993: 2987: 2975: 2972: 2969: 2949: 2939: 2936: 2917: 2914: 2911: 2891: 2888: 2885: 2882: 2879: 2876: 2873: 2870: 2867: 2864: 2861: 2858: 2855: 2852: 2828: 2808: 2805: 2802: 2782: 2779: 2776: 2773: 2770: 2767: 2764: 2761: 2758: 2755: 2752: 2749: 2746: 2743: 2723: 2703: 2679: 2656: 2636: 2616: 2596: 2576: 2573: 2570: 2567: 2564: 2561: 2558: 2555: 2544: 2543: 2531: 2528: 2525: 2505: 2495: 2492: 2486: 2474: 2471: 2468: 2448: 2438: 2435: 2429: 2417: 2414: 2411: 2391: 2381: 2378: 2372: 2360: 2357: 2354: 2334: 2324: 2321: 2302: 2282: 2251: 2248: 2246: 2243: 2227: 2224: 2221: 2218: 2215: 2212: 2209: 2206: 2203: 2200: 2197: 2194: 2189: 2186: 2182: 2178: 2175: 2172: 2167: 2163: 2159: 2158: 2155: 2152: 2149: 2146: 2143: 2140: 2137: 2134: 2131: 2128: 2125: 2122: 2117: 2114: 2110: 2106: 2103: 2100: 2095: 2091: 2087: 2086: 2066: 2061: 2057: 2053: 2048: 2044: 2040: 2034: 2031: 2006: 2003: 1999: 1970: 1966: 1943: 1939: 1918: 1894: 1889: 1885: 1881: 1878: 1873: 1869: 1866: 1863: 1860: 1857: 1854: 1848: 1843: 1839: 1836: 1833: 1830: 1827: 1824: 1818: 1813: 1809: 1805: 1802: 1797: 1793: 1789: 1784: 1780: 1776: 1773: 1771: 1769: 1766: 1765: 1762: 1757: 1754: 1749: 1744: 1740: 1737: 1734: 1731: 1728: 1725: 1719: 1714: 1710: 1706: 1701: 1697: 1694: 1691: 1688: 1685: 1682: 1676: 1673: 1671: 1667: 1663: 1659: 1658: 1655: 1650: 1647: 1642: 1637: 1633: 1630: 1627: 1624: 1621: 1618: 1612: 1607: 1603: 1599: 1594: 1590: 1587: 1584: 1581: 1578: 1575: 1569: 1566: 1564: 1560: 1556: 1552: 1551: 1531: 1527: 1523: 1520: 1517: 1514: 1511: 1508: 1505: 1502: 1499: 1496: 1493: 1490: 1487: 1484: 1462: 1458: 1454: 1449: 1445: 1420: 1415: 1411: 1405: 1402: 1397: 1393: 1386: 1383: 1380: 1377: 1374: 1371: 1367: 1363: 1360: 1358: 1354: 1350: 1346: 1345: 1342: 1337: 1333: 1327: 1324: 1319: 1315: 1308: 1305: 1302: 1299: 1296: 1293: 1289: 1285: 1282: 1280: 1276: 1272: 1268: 1267: 1245: 1241: 1215: 1211: 1187: 1164: 1144: 1141: 1136: 1133: 1130: 1127: 1123: 1101: 1095: 1092: 1089: 1086: 1082: 1077: 1073: 1070: 1067: 1063: 1057: 1054: 1051: 1048: 1044: 1039: 1018: 1015: 1012: 1009: 1006: 1003: 1000: 997: 994: 991: 988: 985: 982: 979: 976: 973: 970: 949: 943: 939: 934: 930: 926: 920: 916: 911: 890: 868: 864: 852: 851: 839: 819: 808: 797: 792: 788: 784: 779: 775: 771: 768: 765: 760: 755: 752: 749: 745: 741: 738: 718: 704:test statistic 691: 688: 685: 665: 662: 659: 656: 653: 650: 647: 644: 624: 621: 618: 598: 595: 592: 589: 586: 583: 580: 556: 545: 531: 527: 523: 520: 517: 512: 508: 486: 480: 476: 471: 467: 464: 461: 457: 451: 447: 442: 430: 419: 415: 409: 405: 400: 396: 393: 390: 386: 380: 376: 371: 344: 340: 336: 333: 330: 325: 321: 306:ordered metric 291: 287: 283: 278: 274: 253: 248: 244: 240: 235: 231: 227: 212:interval scale 199: 194: 190: 186: 181: 177: 173: 170: 167: 164: 161: 156: 152: 148: 143: 139: 135: 119: 118:Test procedure 116: 92:Frank Wilcoxon 87: 84: 32:non-parametric 15: 9: 6: 4: 3: 2: 14782: 14771: 14768: 14766: 14763: 14761: 14758: 14757: 14755: 14740: 14739: 14730: 14728: 14727: 14718: 14716: 14715: 14710: 14704: 14702: 14701: 14692: 14691: 14688: 14674: 14671: 14669: 14668:Geostatistics 14666: 14664: 14661: 14659: 14656: 14654: 14651: 14650: 14648: 14646: 14642: 14636: 14635:Psychometrics 14633: 14631: 14628: 14626: 14623: 14621: 14618: 14616: 14613: 14611: 14608: 14606: 14603: 14601: 14598: 14596: 14593: 14591: 14588: 14587: 14585: 14583: 14579: 14573: 14570: 14568: 14565: 14563: 14559: 14556: 14554: 14551: 14549: 14546: 14544: 14541: 14540: 14538: 14536: 14532: 14526: 14523: 14521: 14518: 14516: 14512: 14509: 14507: 14504: 14503: 14501: 14499: 14498:Biostatistics 14495: 14491: 14487: 14482: 14478: 14460: 14459:Log-rank test 14457: 14456: 14454: 14450: 14444: 14441: 14440: 14438: 14436: 14432: 14426: 14423: 14421: 14418: 14416: 14413: 14411: 14408: 14407: 14405: 14403: 14399: 14396: 14394: 14390: 14380: 14377: 14375: 14372: 14370: 14367: 14365: 14362: 14360: 14357: 14356: 14354: 14352: 14348: 14342: 14339: 14337: 14334: 14332: 14330:(Box–Jenkins) 14326: 14324: 14321: 14319: 14316: 14312: 14309: 14308: 14307: 14304: 14303: 14301: 14299: 14295: 14289: 14286: 14284: 14283:Durbin–Watson 14281: 14279: 14273: 14271: 14268: 14266: 14265:Dickey–Fuller 14263: 14262: 14260: 14256: 14250: 14247: 14245: 14242: 14240: 14239:Cointegration 14237: 14235: 14232: 14230: 14227: 14225: 14222: 14220: 14217: 14215: 14214:Decomposition 14212: 14211: 14209: 14205: 14202: 14200: 14196: 14186: 14183: 14182: 14181: 14178: 14177: 14176: 14173: 14169: 14166: 14165: 14164: 14161: 14159: 14156: 14154: 14151: 14149: 14146: 14144: 14141: 14139: 14136: 14134: 14131: 14129: 14126: 14125: 14123: 14121: 14117: 14111: 14108: 14106: 14103: 14101: 14098: 14096: 14093: 14091: 14088: 14086: 14085:Cohen's kappa 14083: 14082: 14080: 14078: 14074: 14070: 14066: 14062: 14058: 14054: 14049: 14045: 14031: 14028: 14026: 14023: 14021: 14018: 14016: 14013: 14012: 14010: 14008: 14004: 13998: 13994: 13990: 13984: 13982: 13979: 13978: 13976: 13974: 13970: 13964: 13961: 13959: 13956: 13954: 13951: 13949: 13946: 13944: 13941: 13939: 13938:Nonparametric 13936: 13934: 13931: 13930: 13928: 13924: 13918: 13915: 13913: 13910: 13908: 13905: 13903: 13900: 13899: 13897: 13895: 13891: 13885: 13882: 13880: 13877: 13875: 13872: 13870: 13867: 13865: 13862: 13861: 13859: 13857: 13853: 13847: 13844: 13842: 13839: 13837: 13834: 13832: 13829: 13828: 13826: 13824: 13820: 13816: 13809: 13806: 13804: 13801: 13800: 13796: 13792: 13776: 13773: 13772: 13771: 13768: 13766: 13763: 13761: 13758: 13754: 13751: 13749: 13746: 13745: 13744: 13741: 13740: 13738: 13736: 13732: 13722: 13719: 13715: 13709: 13707: 13701: 13699: 13693: 13692: 13691: 13688: 13687:Nonparametric 13685: 13683: 13677: 13673: 13670: 13669: 13668: 13662: 13658: 13657:Sample median 13655: 13654: 13653: 13650: 13649: 13647: 13645: 13641: 13633: 13630: 13628: 13625: 13623: 13620: 13619: 13618: 13615: 13613: 13610: 13608: 13602: 13600: 13597: 13595: 13592: 13590: 13587: 13585: 13582: 13580: 13578: 13574: 13572: 13569: 13568: 13566: 13564: 13560: 13554: 13552: 13548: 13546: 13544: 13539: 13537: 13532: 13528: 13527: 13524: 13521: 13519: 13515: 13505: 13502: 13500: 13497: 13495: 13492: 13491: 13489: 13487: 13483: 13477: 13474: 13470: 13467: 13466: 13465: 13462: 13458: 13455: 13454: 13453: 13450: 13448: 13445: 13444: 13442: 13440: 13436: 13428: 13425: 13423: 13420: 13419: 13418: 13415: 13413: 13410: 13408: 13405: 13403: 13400: 13398: 13395: 13393: 13390: 13389: 13387: 13385: 13381: 13375: 13372: 13368: 13365: 13361: 13358: 13356: 13353: 13352: 13351: 13348: 13347: 13346: 13343: 13339: 13336: 13334: 13331: 13329: 13326: 13324: 13321: 13320: 13319: 13316: 13315: 13313: 13311: 13307: 13304: 13302: 13298: 13292: 13289: 13287: 13284: 13280: 13277: 13276: 13275: 13272: 13270: 13267: 13263: 13262:loss function 13260: 13259: 13258: 13255: 13251: 13248: 13246: 13243: 13241: 13238: 13237: 13236: 13233: 13231: 13228: 13226: 13223: 13219: 13216: 13214: 13211: 13209: 13203: 13200: 13199: 13198: 13195: 13191: 13188: 13186: 13183: 13181: 13178: 13177: 13176: 13173: 13169: 13166: 13164: 13161: 13160: 13159: 13156: 13152: 13149: 13148: 13147: 13144: 13140: 13137: 13136: 13135: 13132: 13130: 13127: 13125: 13122: 13120: 13117: 13116: 13114: 13112: 13108: 13104: 13100: 13095: 13091: 13077: 13074: 13072: 13069: 13067: 13064: 13062: 13059: 13058: 13056: 13054: 13050: 13044: 13041: 13039: 13036: 13034: 13031: 13030: 13028: 13024: 13018: 13015: 13013: 13010: 13008: 13005: 13003: 13000: 12998: 12995: 12993: 12990: 12988: 12985: 12984: 12982: 12980: 12976: 12970: 12967: 12965: 12964:Questionnaire 12962: 12960: 12957: 12953: 12950: 12948: 12945: 12944: 12943: 12940: 12939: 12937: 12935: 12931: 12925: 12922: 12920: 12917: 12915: 12912: 12910: 12907: 12905: 12902: 12900: 12897: 12895: 12892: 12890: 12887: 12886: 12884: 12882: 12878: 12874: 12870: 12865: 12861: 12847: 12844: 12842: 12839: 12837: 12834: 12832: 12829: 12827: 12824: 12822: 12819: 12817: 12814: 12812: 12809: 12807: 12804: 12802: 12799: 12797: 12794: 12792: 12791:Control chart 12789: 12787: 12784: 12782: 12779: 12777: 12774: 12773: 12771: 12769: 12765: 12759: 12756: 12752: 12749: 12747: 12744: 12743: 12742: 12739: 12737: 12734: 12732: 12729: 12728: 12726: 12724: 12720: 12714: 12711: 12709: 12706: 12704: 12701: 12700: 12698: 12694: 12688: 12685: 12684: 12682: 12680: 12676: 12664: 12661: 12659: 12656: 12654: 12651: 12650: 12649: 12646: 12644: 12641: 12640: 12638: 12636: 12632: 12626: 12623: 12621: 12618: 12616: 12613: 12611: 12608: 12606: 12603: 12601: 12598: 12596: 12593: 12592: 12590: 12588: 12584: 12578: 12575: 12573: 12570: 12566: 12563: 12561: 12558: 12556: 12553: 12551: 12548: 12546: 12543: 12541: 12538: 12536: 12533: 12531: 12528: 12526: 12523: 12521: 12518: 12517: 12516: 12513: 12512: 12510: 12508: 12504: 12501: 12499: 12495: 12491: 12487: 12482: 12478: 12472: 12469: 12467: 12464: 12463: 12460: 12456: 12449: 12444: 12442: 12437: 12435: 12430: 12429: 12426: 12420: 12416: 12412: 12409: 12406: 12404: 12401: 12399: 12396: 12394: 12391: 12389: 12386: 12385: 12366: 12362: 12356: 12348: 12342: 12338: 12337: 12329: 12321: 12315: 12306: 12301: 12298:: 11.IT.3.1, 12297: 12293: 12286: 12284: 12274: 12265: 12256: 12250:Siegel, p. 76 12247: 12238: 12229: 12221: 12217: 12213: 12209: 12202: 12193: 12184: 12175: 12170: 12166: 12162: 12158: 12151: 12149: 12139: 12130: 12121: 12112: 12103: 12094: 12085: 12076: 12067: 12061: 12057: 12050: 12044:Pratt, p. 660 12041: 12035:Pratt, p. 661 12032: 12023: 12014: 12008:Pratt, p. 660 12005: 11996: 11987: 11978: 11969: 11963:Pratt, p. 660 11960: 11951: 11942: 11933: 11924: 11916: 11912: 11908: 11904: 11897: 11889: 11885: 11878: 11872:Pratt, p. 663 11869: 11863:Pratt, p. 659 11860: 11852: 11848: 11844: 11840: 11833: 11825: 11818: 11809: 11800: 11791: 11782: 11776: 11772: 11768: 11762: 11753: 11744: 11735: 11726: 11717: 11708: 11699: 11690: 11688:0-471-88474-X 11684: 11680: 11673: 11664: 11655: 11646: 11637: 11628: 11622: 11618: 11611: 11602: 11596:Siegel, p. 76 11593: 11584: 11576: 11574:9780070573482 11570: 11566: 11565: 11557: 11549: 11545: 11541: 11537: 11533: 11529: 11525: 11521: 11514: 11507: 11493: 11489: 11483: 11474: 11472:0-471-16068-7 11468: 11464: 11457: 11453: 11443: 11440: 11438: 11435: 11434: 11424: 11421: 11414: 11411: 11403: 11400: 11397: 11394: 11391: 11388: 11384:wilcoxon_test 11381: 11378: 11375: 11372: 11336: 11333: 11332: 11326: 11324: 11320: 11316: 11312: 11308: 11303: 11298: 11296: 11292: 11288: 11284: 11280: 11277: =  11276: 11272: 11268: 11264: 11259: 11257: 11253: 11247: 11223: 11203: 11195: 11178: 11174: 11165: 11158: 11144: 11141: 11128: 11122: 11119: 11116: 11113: 11107: 11104: 11100: 11096: 11088: 11076: 11062: 11059: 11056: 11053: 11050: 11047: 11044: 11041: 11038: 11035: 11032: 11029: 11026: 11023: 11020: 11017: 11014: 11011: 11008: 11005: 11002: 10995: 10994: 10993: 10991: 10973: 10969: 10960: 10934: 10933:sign function 10918: 10901: 10898: 10895: 10892: 10889: 10886: 10883: 10882: 10878: 10875: 10872: 10869: 10866: 10863: 10860: 10859: 10855: 10852: 10849: 10846: 10843: 10840: 10837: 10836: 10832: 10829: 10826: 10823: 10820: 10817: 10814: 10813: 10809: 10806: 10803: 10800: 10797: 10794: 10791: 10790: 10786: 10783: 10780: 10777: 10774: 10771: 10768: 10767: 10763: 10760: 10757: 10754: 10751: 10748: 10745: 10744: 10740: 10737: 10734: 10731: 10728: 10725: 10722: 10721: 10717: 10714: 10711: 10708: 10705: 10702: 10699: 10698: 10694: 10691: 10688: 10685: 10682: 10679: 10676: 10675: 10658: 10654: 10650: 10647: 10640: 10624: 10620: 10612: 10589: 10575: 10568: 10567: 10550: 10547: 10544: 10540: 10536: 10531: 10528: 10525: 10521: 10497: 10494: 10491: 10487: 10463: 10460: 10457: 10453: 10431: 10423: 10420: 10417: 10410: 10407: 10404: 10401: 10398: 10397: 10393: 10390: 10387: 10384: 10381: 10380: 10376: 10373: 10370: 10367: 10364: 10363: 10359: 10356: 10353: 10350: 10347: 10346: 10342: 10339: 10336: 10333: 10330: 10329: 10325: 10322: 10319: 10316: 10313: 10312: 10308: 10305: 10302: 10299: 10296: 10295: 10291: 10288: 10285: 10282: 10279: 10278: 10274: 10271: 10268: 10265: 10262: 10261: 10257: 10254: 10251: 10248: 10245: 10244: 10220: 10206: 10199: 10198: 10181: 10178: 10175: 10171: 10167: 10162: 10159: 10156: 10152: 10128: 10125: 10122: 10118: 10094: 10091: 10088: 10084: 10062: 10054: 10051: 10050: 10042: 10026: 10022: 9995: 9992: 9989: 9983: 9976: 9970: 9965: 9961: 9957: 9937: 9915: 9911: 9888: 9884: 9863: 9841: 9836: 9832: 9809: 9804: 9800: 9777: 9773: 9764: 9748: 9745: 9742: 9734: 9729: 9710: 9706: 9702: 9697: 9693: 9672: 9655: 9651: 9645: 9641: 9637: 9635: 9625: 9621: 9614: 9611: 9604: 9599: 9595: 9591: 9589: 9581: 9575: 9572: 9548: 9543: 9539: 9535: 9531: 9528: 9522: 9519: 9516: 9513: 9504: 9501: 9498: 9492: 9489: 9483: 9480: 9477: 9474: 9465: 9462: 9459: 9453: 9447: 9442: 9438: 9417: 9412: 9405: 9402: 9399: 9393: 9387: 9382: 9375: 9372: 9369: 9363: 9357: 9349: 9345: 9314: 9310: 9289: 9269: 9249: 9246: 9243: 9238: 9234: 9230: 9227: 9224: 9204: 9184: 9164: 9155: 9142: 9134: 9131: 9127: 9123: 9120: 9112: 9107: 9104: 9101: 9097: 9089: 9085: 9081: 9076: 9070: 9064: 9044: 9035: 9016: 9012: 9008: 9005: 9001: 8994: 8972: 8968: 8947: 8940: 8933: 8930: 8927: 8924: 8915: 8912: 8909: 8903: 8894: 8887: 8884: 8881: 8875: 8869: 8863: 8860: 8854: 8851: 8845: 8842: 8822: 8816: 8813: 8810: 8805: 8801: 8781: 8778: 8775: 8772: 8763: 8760: 8757: 8751: 8748: 8743: 8740: 8737: 8734: 8731: 8726: 8722: 8718: 8702: 8696: 8693: 8687: 8678: 8672: 8669: 8664: 8660: 8644: 8627: 8622: 8615: 8612: 8609: 8606: 8597: 8594: 8591: 8585: 8579: 8577: 8569: 8563: 8560: 8553: 8548: 8541: 8538: 8535: 8532: 8523: 8520: 8517: 8511: 8505: 8497: 8493: 8486: 8483: 8480: 8478: 8468: 8464: 8457: 8454: 8447: 8444: 8441: 8439: 8431: 8416: 8411: 8404: 8401: 8398: 8392: 8386: 8378: 8374: 8362: 8360: 8350: 8346: 8311: 8307: 8284: 8280: 8259: 8239: 8230: 8211: 8207: 8203: 8198: 8194: 8164: 8161: 8156: 8152: 8143: 8140: 8137: 8133: 8129: 8121: 8117: 8108: 8105: 8102: 8098: 8094: 8086: 8082: 8073: 8069: 8065: 8040: 8036: 8027: 8023: 8002: 7980: 7976: 7972: 7967: 7963: 7937: 7933: 7924: 7920: 7910: 7908: 7890: 7886: 7863: 7859: 7854: 7845: 7841: 7832: 7828: 7824: 7816: 7812: 7808: 7803: 7799: 7770: 7766: 7745: 7742: 7737: 7733: 7709: 7706: 7703: 7700: 7697: 7694: 7691: 7668: 7648: 7625: 7622: 7619: 7616: 7613: 7610: 7607: 7584: 7562: 7558: 7534: 7531: 7528: 7525: 7522: 7499: 7493: 7490: 7485: 7481: 7472: 7469: 7466: 7462: 7458: 7450: 7446: 7437: 7434: 7431: 7427: 7423: 7415: 7411: 7402: 7398: 7377: 7373: 7366: 7363: 7360: 7354: 7351: 7348: 7328: 7325: 7322: 7302: 7299: 7291: 7287: 7278: 7274: 7253: 7250: 7245: 7241: 7220: 7217: 7209: 7205: 7196: 7192: 7171: 7168: 7162: 7154: 7150: 7127: 7123: 7115:which sum to 7099: 7096: 7093: 7090: 7087: 7062: 7058: 7054: 7049: 7045: 7019: 7015: 7006: 7002: 6979: 6975: 6954: 6932: 6928: 6907: 6898: 6884: 6862: 6858: 6837: 6834: 6831: 6811: 6808: 6805: 6783: 6779: 6758: 6738: 6730: 6720: 6718: 6714: 6710: 6706: 6690: 6682: 6677: 6661: 6657: 6652: 6648: 6645: 6642: 6630: 6629: 6628: 6612: 6608: 6603: 6599: 6596: 6593: 6581: 6580: 6579: 6573: 6572: 6571: 6568: 6548: 6523: 6503: 6483: 6475: 6470: 6466: 6464: 6445: 6442: 6439: 6436: 6433: 6421: 6407: 6397: 6383: 6379: 6372: 6369: 6366: 6343: 6323: 6303: 6283: 6263: 6243: 6223: 6220: 6217: 6197: 6177: 6174: 6171: 6167: 6160: 6157: 6154: 6151: 6148: 6123: 6119: 6096: 6092: 6069: 6065: 6042: 6038: 6017: 6014: 6011: 6007: 6000: 5997: 5994: 5969: 5965: 5942: 5938: 5915: 5911: 5890: 5880: 5876: 5867: 5857: 5853: 5844: 5834: 5830: 5821: 5811: 5807: 5798: 5788: 5784: 5775: 5765: 5761: 5752: 5742: 5738: 5723: 5706: 5703: 5700: 5697: 5694: 5682: 5678: 5674: 5669: 5653: 5649: 5634: 5617: 5614: 5601: 5599: 5594: 5592: 5587: 5573: 5553: 5530: 5527: 5522: 5518: 5514: 5509: 5505: 5475: 5472: 5467: 5463: 5459: 5454: 5450: 5423: 5420: 5417: 5392: 5372: 5364: 5360: 5345: 5337: 5334: 5333: 5332: 5318: 5315: 5309: 5303: 5300: 5292: 5287: 5285: 5281: 5263: 5259: 5254: 5250: 5228: 5224: 5219: 5215: 5195: 5175: 5172: 5167: 5163: 5158: 5154: 5151: 5148: 5126: 5122: 5117: 5113: 5105: 5097: 5096: 5095: 5081: 5078: 5073: 5069: 5064: 5060: 5057: 5054: 5032: 5028: 5023: 5019: 5011: 5003: 5002: 5001: 4995: 4994: 4993: 4989: 4988: 4977: 4961: 4957: 4934: 4930: 4926: 4921: 4917: 4913: 4908: 4904: 4900: 4895: 4891: 4868: 4864: 4860: 4855: 4851: 4830: 4827: 4824: 4802: 4798: 4794: 4789: 4785: 4759: 4755: 4751: 4746: 4742: 4716: 4712: 4679: 4676: 4671: 4667: 4663: 4658: 4654: 4644: 4638: 4635: 4630: 4626: 4622: 4617: 4613: 4606: 4603: 4583: 4580: 4577: 4555: 4551: 4547: 4542: 4538: 4529: 4524: 4520: 4502: 4499: 4494: 4490: 4486: 4481: 4477: 4467: 4461: 4458: 4453: 4449: 4445: 4440: 4436: 4429: 4426: 4406: 4403: 4400: 4378: 4374: 4370: 4365: 4361: 4352: 4347: 4343: 4323: 4319: 4315: 4310: 4306: 4294: 4289: 4285: 4284: 4283: 4280: 4264: 4260: 4256: 4251: 4247: 4224: 4220: 4216: 4211: 4207: 4178: 4175: 4170: 4166: 4162: 4159: 4156: 4151: 4147: 4118: 4114: 4110: 4105: 4101: 4077: 4074: 4071: 4063: 4058: 4054: 4036: 4033: 4028: 4024: 4020: 4017: 4014: 4009: 4005: 3976: 3972: 3968: 3963: 3959: 3935: 3932: 3929: 3921: 3916: 3912: 3894: 3891: 3886: 3882: 3878: 3875: 3872: 3867: 3863: 3834: 3830: 3826: 3821: 3817: 3793: 3790: 3787: 3779: 3774: 3770: 3752: 3749: 3746: 3740: 3737: 3731: 3728: 3725: 3719: 3694: 3690: 3686: 3681: 3677: 3648: 3644: 3640: 3635: 3631: 3619: 3598: 3594: 3590: 3585: 3581: 3569: 3564: 3560: 3559: 3558: 3540: 3537: 3534: 3512: 3508: 3504: 3499: 3495: 3486: 3481: 3477: 3462: 3459: 3456: 3434: 3430: 3426: 3421: 3417: 3408: 3403: 3399: 3384: 3381: 3378: 3356: 3352: 3348: 3343: 3339: 3330: 3325: 3321: 3306: 3303: 3300: 3278: 3274: 3270: 3265: 3261: 3252: 3247: 3243: 3242: 3241: 3222: 3218: 3214: 3209: 3205: 3178: 3175: 3172: 3166: 3157: 3141: 3137: 3133: 3128: 3124: 3108: 3092: 3088: 3065: 3061: 3035: 3028: 3023: 3019: 3004: 2997: 2992: 2988: 2973: 2970: 2967: 2947: 2940: 2935: 2931: 2930: 2929: 2915: 2912: 2909: 2886: 2883: 2880: 2871: 2865: 2862: 2859: 2856: 2842: 2826: 2819:. Similarly, 2806: 2803: 2800: 2777: 2774: 2771: 2762: 2756: 2753: 2750: 2747: 2721: 2701: 2693: 2677: 2668: 2654: 2634: 2614: 2594: 2574: 2571: 2565: 2562: 2559: 2529: 2526: 2523: 2503: 2496: 2491: 2487: 2472: 2469: 2466: 2446: 2439: 2434: 2430: 2415: 2412: 2409: 2389: 2382: 2377: 2373: 2358: 2355: 2352: 2332: 2325: 2320: 2316: 2315: 2314: 2300: 2280: 2272: 2267: 2265: 2261: 2257: 2242: 2225: 2219: 2216: 2213: 2210: 2207: 2204: 2201: 2198: 2195: 2192: 2187: 2184: 2180: 2170: 2165: 2161: 2153: 2147: 2144: 2141: 2138: 2135: 2132: 2129: 2126: 2123: 2120: 2115: 2112: 2108: 2098: 2093: 2089: 2059: 2055: 2051: 2046: 2042: 2032: 2029: 2004: 2001: 1997: 1989: 1988:Walsh average 1984: 1968: 1964: 1941: 1937: 1916: 1892: 1887: 1883: 1879: 1876: 1871: 1864: 1861: 1858: 1852: 1846: 1841: 1834: 1831: 1828: 1822: 1816: 1811: 1807: 1803: 1800: 1795: 1791: 1787: 1782: 1778: 1774: 1772: 1767: 1760: 1755: 1752: 1747: 1742: 1735: 1732: 1729: 1723: 1717: 1712: 1708: 1704: 1699: 1692: 1689: 1686: 1680: 1674: 1672: 1665: 1661: 1653: 1648: 1645: 1640: 1635: 1628: 1625: 1622: 1616: 1610: 1605: 1601: 1597: 1592: 1585: 1582: 1579: 1573: 1567: 1565: 1558: 1554: 1529: 1525: 1518: 1515: 1512: 1506: 1503: 1500: 1497: 1494: 1491: 1488: 1485: 1482: 1460: 1456: 1452: 1447: 1443: 1418: 1413: 1409: 1403: 1400: 1395: 1391: 1384: 1381: 1378: 1375: 1372: 1369: 1365: 1361: 1359: 1352: 1348: 1340: 1335: 1331: 1325: 1322: 1317: 1313: 1306: 1303: 1300: 1297: 1294: 1291: 1287: 1283: 1281: 1274: 1270: 1243: 1239: 1231: 1213: 1209: 1201: 1185: 1176: 1162: 1142: 1139: 1131: 1125: 1121: 1090: 1084: 1080: 1071: 1068: 1065: 1052: 1046: 1042: 1029:is such that 1013: 1010: 1007: 1004: 1001: 989: 986: 983: 980: 977: 971: 968: 941: 937: 928: 918: 914: 888: 866: 862: 837: 817: 809: 795: 790: 786: 777: 773: 766: 763: 758: 753: 750: 747: 743: 739: 736: 716: 709: 705: 689: 686: 683: 663: 660: 657: 651: 645: 642: 622: 619: 616: 596: 593: 587: 581: 578: 570: 569:sign function 554: 546: 529: 525: 521: 518: 515: 510: 506: 478: 474: 465: 462: 459: 449: 445: 431: 417: 407: 403: 394: 391: 388: 378: 374: 360: 359: 358: 342: 338: 334: 331: 328: 323: 319: 309: 307: 289: 285: 281: 276: 272: 246: 242: 238: 233: 229: 217: 213: 192: 188: 184: 179: 175: 168: 165: 162: 154: 150: 146: 141: 137: 124: 123:paired data. 115: 113: 111: 105: 101: 100:Sidney Siegel 97: 96:rank-sum test 93: 83: 81: 76: 72: 68: 64: 60: 56: 52: 50: 44: 40: 36: 33: 29: 22: 14770:U-statistics 14736: 14724: 14705: 14698: 14610:Econometrics 14560: / 14543:Chemometrics 14520:Epidemiology 14513: / 14486:Applications 14328:ARIMA model 14275:Q-statistic 14224:Stationarity 14120:Multivariate 14063: / 14059: / 14057:Multivariate 14055: / 13995: / 13991: / 13765:Bayes factor 13664:Signed rank 13663: 13576: 13550: 13542: 13530: 13225:Completeness 13061:Cohort study 12959:Opinion poll 12894:Missing data 12881:Study design 12836:Scatter plot 12758:Scatter plot 12751:Spearman's ρ 12713:Grouped data 12414: 12368:. Retrieved 12364: 12355: 12335: 12328: 12295: 12291: 12273: 12264: 12255: 12246: 12237: 12228: 12211: 12207: 12201: 12192: 12183: 12164: 12160: 12138: 12129: 12120: 12111: 12102: 12093: 12084: 12075: 12055: 12049: 12040: 12031: 12022: 12013: 12004: 11995: 11986: 11977: 11968: 11959: 11950: 11941: 11932: 11923: 11906: 11902: 11896: 11887: 11883: 11877: 11868: 11859: 11842: 11838: 11832: 11823: 11817: 11808: 11799: 11790: 11770: 11761: 11752: 11743: 11734: 11725: 11716: 11707: 11698: 11693:, pp. 32, 50 11678: 11672: 11663: 11654: 11645: 11636: 11616: 11610: 11601: 11592: 11583: 11563: 11556: 11526:(6): 80–83. 11523: 11519: 11506: 11495:. Retrieved 11491: 11482: 11462: 11456: 11322: 11318: 11314: 11310: 11306: 11301: 11299: 11294: 11290: 11286: 11282: 11278: 11274: 11270: 11266: 11262: 11260: 11249: 10911: 9762: 9732: 9730: 9678: 9156: 9036: 8645: 8231: 7911: 6899: 6728: 6726: 6716: 6712: 6708: 6707:method, the 6704: 6680: 6678: 6634: 6585: 6577: 6569: 6473: 6468: 6467: 6462: 6422: 6398: 5724: 5680: 5676: 5673:average rank 5672: 5670: 5640: 5602: 5598:Likert scale 5595: 5590: 5588: 5408: 5362:observation. 5290: 5288: 5283: 5279: 5103: 5101: 5009: 5007: 4999: 4990: 4986: 4983: 4703: 4522: 4345: 4287: 4281: 4197: 4090:, the pairs 4056: 3948:, the pairs 3914: 3806:, the pairs 3772: 3618:exchangeable 3617: 3562: 3556: 3479: 3401: 3323: 3245: 3158: 3114: 3051: 3021: 2990: 2933: 2840: 2691: 2669: 2545: 2489: 2432: 2375: 2318: 2268: 2264:pseudomedian 2253: 1987: 1985: 1229: 1199: 1177: 853: 707: 310: 305: 216:real numbers 125: 121: 109: 107: 103: 89: 66: 62: 58: 48: 27: 25: 14738:WikiProject 14653:Cartography 14615:Jurimetrics 14567:Reliability 14298:Time domain 14277:(Ljung–Box) 14199:Time-series 14077:Categorical 14061:Time-series 14053:Categorical 13988:(Bernoulli) 13823:Correlation 13803:Correlation 13599:Jarque–Bera 13571:Chi-squared 13333:M-estimator 13286:Asymptotics 13230:Sufficiency 12997:Interaction 12909:Replication 12889:Effect size 12846:Violin plot 12826:Radar chart 12806:Forest plot 12796:Correlogram 12746:Kendall's τ 11785:, pp. 39–41 11340:wilcox.test 11252:effect size 11240:Effect size 11133:, two-sided 6256:, and that 5208:is between 567:denote the 14754:Categories 14605:Demography 14323:ARMA model 14128:Regression 13705:(Friedman) 13666:(Wilcoxon) 13604:Normality 13594:Lilliefors 13541:Student's 13417:Resampling 13291:Robustness 13279:divergence 13269:Efficiency 13207:(monotone) 13202:Likelihood 13119:Population 12952:Stratified 12904:Population 12723:Dependence 12679:Count data 12610:Percentile 12587:Dispersion 12520:Arithmetic 12455:Statistics 12370:2023-08-24 11890:(3): 1–13. 11497:2021-09-02 11448:References 11396:Accord.NET 11380:GNU Octave 11273:, or  7785:satisfies 6727:Computing 5280:decreasing 5106:-value of 5012:-value of 4843:, we have 2734:satisfies 901:for which 810:Produce a 47:Student's 13986:Logistic 13753:posterior 13679:Rank sum 13427:Jackknife 13422:Bootstrap 13240:Bootstrap 13175:Parameter 13124:Statistic 12919:Statistic 12831:Run chart 12816:Pie chart 12811:Histogram 12801:Fan chart 12776:Bar chart 12658:L-moments 12545:Geometric 11442:Sign test 11386:function. 11166:∴ 11114:α 11108:⁡ 11036:− 11030:− 11024:− 11018:− 10833: –6 10824: –1 10810: –5 10801: –1 10787: –4 10778: –1 10764: –3 10755: –1 10651:⋅ 10537:− 10408: –1 10374: –1 10340: –1 10272: –1 10168:− 9993:− 9916:− 9842:− 9746:− 9711:− 9642:σ 9615:⁡ 9596:σ 9576:⁡ 9529:− 9490:− 9439:σ 9388:− 9244:− 9231:∑ 9098:∏ 9006:− 8870:− 8811:− 8741:− 8697:ϕ 8682:Φ 8679:≈ 8670:≤ 8564:⁡ 8498:− 8487:⁡ 8458:⁡ 8379:− 8312:− 8204:≤ 8162:− 8141:− 8106:− 7743:− 7707:− 7698:… 7623:− 7614:… 7529:… 7491:− 7470:− 7435:− 7251:≠ 7094:… 6994:. Define 6719:-values. 6643:α 6594:α 6465:-values. 6440:… 6408:μ 6373:ℓ 6344:ℓ 6264:ℓ 6221:− 5701:… 5421:≠ 5393:α 5373:α 5346:μ 5304:⁡ 5196:α 5173:≈ 5149:α 5079:≈ 5055:α 4927:− 4901:− 4828:≠ 4645:≤ 4636:− 4581:≥ 4548:− 4468:≥ 4459:− 4404:≥ 4371:− 4257:− 4217:− 4179:μ 4176:− 4160:μ 4075:≠ 4072:μ 4064:For some 4037:μ 4034:− 4018:μ 3930:μ 3922:For some 3895:μ 3892:− 3876:μ 3788:μ 3780:For some 3538:≠ 3535:μ 3505:− 3457:μ 3427:− 3379:μ 3349:− 3301:μ 3271:− 3134:− 3089:μ 3062:μ 2968:μ 2913:≥ 2872:≤ 2863:− 2804:≥ 2763:≥ 2754:− 2655:μ 2595:μ 2566:μ 2527:≠ 2524:μ 2467:μ 2410:μ 2353:μ 2217:≤ 2211:≤ 2205:≤ 2199:: 2174:# 2166:− 2145:≤ 2139:≤ 2133:≤ 2127:: 2102:# 1969:− 1888:− 1877:− 1817:− 1796:− 1788:− 1748:− 1705:− 1666:− 1606:− 1598:− 1495:⋯ 1461:− 1379:≤ 1373:≤ 1366:∑ 1353:− 1301:≤ 1295:≤ 1288:∑ 1244:− 1126:σ 1085:σ 1069:⋯ 1047:σ 1008:… 996:→ 984:… 969:σ 929:≤ 767:⁡ 744:∑ 661:− 646:⁡ 582:⁡ 519:… 463:… 392:… 332:… 282:− 166:… 108:Wilcoxon 80:sign test 73:when the 35:rank test 14700:Category 14393:Survival 14270:Johansen 13993:Binomial 13948:Isotonic 13535:(normal) 13180:location 12987:Blocking 12942:Sampling 12821:Q–Q plot 12786:Box plot 12768:Graphics 12663:Skewness 12653:Kurtosis 12625:Variance 12555:Heronian 12550:Harmonic 12314:citation 12070:, p. 194 11631:, p. 148 11477:, p. 350 11431:See also 11297:= 0.20. 7315:for all 7233:for all 6336:through 5284:positive 2902:for all 2793:for all 2077:. Then: 1909:Because 1435:Because 1228:and the 1155:for all 361:Compute 43:location 14726:Commons 14673:Kriging 14558:Process 14515:studies 14374:Wavelet 14207:General 13374:Plug-in 13168:L space 12947:Cluster 12648:Moments 12466:Outline 11548:3001968 11325:= .20. 10988:is the 10957:is the 10931:is the 10695:  10692:  10686:  10323:  10045:Example 6210:, that 5278:, then 2587:, then 1113:, then 706:is the 86:History 14595:Census 14185:Normal 14133:Manova 13953:Robust 13703:2-way 13695:1-way 13533:-test 13204:  12781:Biplot 12572:Median 12565:Lehmer 12507:Center 12343:  12062:  11777:  11685:  11623:  11571:  11546:  11469:  11409:level. 11402:MATLAB 11374:ALGLIB 11358:paired 11317:minus 11224:0.6113 11126:  10961:, and 9903:, and 8835:where 8299:, and 7266:, and 6111:, and 5176:0.0133 5082:0.0134 2694:if an 2256:median 2019:to be 1956:, and 1388:  1310:  702:. The 71:t-test 14219:Trend 13748:prior 13690:anova 13579:-test 13553:-test 13545:-test 13452:Power 13397:Pivot 13190:shape 13185:scale 12635:Shape 12615:Range 12560:Heinz 12535:Cubic 12471:Index 11544:JSTOR 11516:(PDF) 11426:test. 11413:Julia 11390:SciPy 9561:then 4980:Zeros 4777:with 2293:. If 432:Sort 112:-test 51:-test 30:is a 14452:Test 13652:Sign 13504:Wald 12577:Mode 12515:Mean 12341:ISBN 12320:link 12060:ISBN 11775:ISBN 11683:ISBN 11621:ISBN 11569:ISBN 11467:ISBN 11364:TRUE 11196:The 11120:0.05 11105:crit 11097:< 10990:rank 10890:120 10887:140 10867:123 10864:140 10844:110 10841:125 10821:137 10818:125 10798:145 10795:135 10775:124 10772:115 10752:122 10749:115 10741:1.5 10738:1.5 10729:135 10726:140 10718:1.5 10715:1.5 10706:125 10703:130 10683:140 10680:140 10405:145 10402:135 10388:135 10385:140 10371:137 10368:125 10354:123 10351:140 10337:124 10334:115 10320:140 10317:140 10303:120 10300:140 10286:125 10283:130 10269:122 10266:115 10252:110 10249:125 7352:> 7326:< 5957:and 5822:< 5799:< 5753:< 5637:Ties 5566:and 5528:< 5491:and 5473:> 5243:and 5152:> 5058:< 4664:> 4623:< 4487:> 4446:< 4136:and 3994:and 3933:> 3852:and 3791:< 3666:and 3616:are 3460:> 3382:< 3159:Let 2884:> 2860:< 2775:> 2751:< 2470:> 2413:< 2262:and 2260:mean 2193:< 2121:> 1401:< 1323:> 1072:< 1066:< 687:< 635:and 620:> 547:Let 37:for 26:The 13632:BIC 13627:AIC 12300:doi 12216:doi 12169:doi 11911:doi 11847:doi 11536:hdl 11528:doi 11423:SAS 11015:1.5 11009:1.5 10944:abs 10919:sgn 10896:20 10873:17 10850:15 10827:12 10804:10 10792:10 10648:sgn 10598:abs 10576:sgn 10411:10 10399:10 10377:12 10360:17 10309:20 10258:15 10229:abs 10207:sgn 9687:min 9612:Var 9573:Var 9430:If 9329:is 8561:Var 8484:Var 8455:Var 7912:If 7341:or 6018:2.5 5675:or 5301:sgn 5216:109 5155:109 5114:109 2843:if 2839:is 2690:is 764:sgn 676:if 643:sgn 609:if 579:sgn 555:sgn 14756:: 12363:. 12316:}} 12312:{{ 12294:, 12282:^ 12212:62 12210:. 12165:24 12163:. 12159:. 12147:^ 11907:68 11905:. 11888:18 11886:. 11843:54 11841:. 11542:. 11534:. 11522:. 11518:. 11490:. 11258:. 11145:15 10935:, 10902:9 10899:9 10893:1 10884:4 10879:8 10876:8 10870:1 10861:7 10856:7 10853:7 10847:1 10838:1 10830:6 10815:8 10807:5 10784:4 10781:9 10769:6 10761:3 10758:7 10746:2 10735:5 10732:1 10723:9 10712:5 10709:1 10700:3 10689:0 10677:5 10394:5 10391:1 10382:9 10365:8 10357:1 10348:7 10343:9 10331:6 10326:0 10314:5 10306:1 10297:4 10292:5 10289:1 10280:3 10275:7 10263:2 10255:1 10246:1 10041:. 9876:, 9656:4. 8941:24 8749:10 8654:Pr 8549:24 8272:, 8229:. 8188:Pr 7909:. 7793:Pr 7184:, 6649:14 6600:14 6396:. 6084:, 6030:, 5586:. 5499:Pr 5444:Pr 5436:, 5286:. 5264:12 5251:55 5229:13 5168:13 5127:13 5074:12 5061:55 5033:12 5020:55 4648:Pr 4596:, 4471:Pr 4419:, 3156:. 3107:. 2875:Pr 2851:Pr 2766:Pr 2742:Pr 2554:Pr 2258:, 1929:, 1175:. 729:: 571:: 114:. 13577:G 13551:F 13543:t 13531:Z 13250:V 13245:U 12447:e 12440:t 12433:v 12373:. 12349:. 12322:) 12302:: 12296:3 12222:. 12218:: 12177:. 12171:: 12068:. 11917:. 11913:: 11853:. 11849:: 11783:. 11691:. 11629:. 11577:. 11550:. 11538:: 11530:: 11524:1 11500:. 11475:. 11419:. 11367:) 11361:= 11355:, 11352:y 11349:, 11346:x 11343:( 11335:R 11323:r 11319:T 11315:S 11311:T 11307:T 11302:T 11295:r 11291:S 11287:T 11283:S 11281:/ 11279:T 11275:r 11271:S 11267:T 11263:T 11204:p 11179:0 11175:H 11142:= 11137:) 11129:9 11123:, 11117:= 11111:( 11101:W 11093:| 11089:W 11085:| 11063:9 11060:= 11057:9 11054:+ 11051:8 11048:+ 11045:7 11042:+ 11039:6 11033:5 11027:4 11021:3 11012:+ 11006:= 11003:W 10974:i 10970:R 10659:i 10655:R 10625:i 10621:R 10551:i 10548:, 10545:1 10541:x 10532:i 10529:, 10526:2 10522:x 10498:i 10495:, 10492:1 10488:x 10464:i 10461:, 10458:2 10454:x 10432:i 10182:i 10179:, 10176:1 10172:x 10163:i 10160:, 10157:2 10153:x 10129:i 10126:, 10123:1 10119:x 10095:i 10092:, 10089:2 10085:x 10063:i 10027:2 10023:p 10002:) 9999:) 9996:1 9990:n 9987:( 9984:n 9981:( 9977:/ 9971:+ 9966:0 9962:T 9958:2 9938:F 9912:T 9889:+ 9885:T 9864:T 9837:0 9833:T 9810:+ 9805:0 9801:T 9778:0 9774:T 9749:1 9743:n 9733:n 9716:) 9707:T 9703:, 9698:+ 9694:T 9690:( 9652:/ 9646:2 9638:= 9631:) 9626:+ 9622:T 9618:( 9605:, 9600:2 9592:= 9585:) 9582:T 9579:( 9549:, 9544:6 9540:2 9536:/ 9532:c 9526:) 9523:1 9520:+ 9517:z 9514:2 9511:( 9508:) 9505:1 9502:+ 9499:z 9496:( 9493:z 9487:) 9484:1 9481:+ 9478:n 9475:2 9472:( 9469:) 9466:1 9463:+ 9460:n 9457:( 9454:n 9448:= 9443:2 9418:. 9413:4 9409:) 9406:1 9403:+ 9400:z 9397:( 9394:z 9383:4 9379:) 9376:1 9373:+ 9370:n 9367:( 9364:n 9358:= 9355:] 9350:+ 9346:T 9342:[ 9338:E 9315:+ 9311:T 9290:T 9270:t 9250:, 9247:t 9239:3 9235:t 9228:= 9225:c 9205:z 9185:n 9165:T 9143:. 9140:) 9135:t 9132:j 9128:e 9124:+ 9121:1 9118:( 9113:n 9108:1 9105:= 9102:j 9090:n 9086:2 9082:1 9077:= 9074:) 9071:t 9068:( 9065:M 9045:T 9022:) 9017:2 9013:/ 9009:3 9002:n 8998:( 8995:O 8973:+ 8969:T 8948:. 8937:) 8934:1 8931:+ 8928:n 8925:2 8922:( 8919:) 8916:1 8913:+ 8910:n 8907:( 8904:n 8895:4 8891:) 8888:1 8885:+ 8882:n 8879:( 8876:n 8864:2 8861:1 8855:+ 8852:k 8846:= 8843:t 8823:, 8820:) 8817:t 8814:3 8806:3 8802:t 8798:( 8793:) 8785:) 8782:1 8779:+ 8776:n 8773:2 8770:( 8767:) 8764:1 8761:+ 8758:n 8755:( 8752:n 8744:1 8738:n 8735:3 8732:+ 8727:2 8723:n 8719:3 8711:( 8706:) 8703:t 8700:( 8694:+ 8691:) 8688:t 8685:( 8676:) 8673:k 8665:+ 8661:T 8657:( 8628:. 8623:6 8619:) 8616:1 8613:+ 8610:n 8607:2 8604:( 8601:) 8598:1 8595:+ 8592:n 8589:( 8586:n 8580:= 8573:) 8570:T 8567:( 8554:, 8545:) 8542:1 8539:+ 8536:n 8533:2 8530:( 8527:) 8524:1 8521:+ 8518:n 8515:( 8512:n 8506:= 8503:) 8494:T 8490:( 8481:= 8474:) 8469:+ 8465:T 8461:( 8448:, 8445:0 8442:= 8435:] 8432:T 8429:[ 8425:E 8417:, 8412:4 8408:) 8405:1 8402:+ 8399:n 8396:( 8393:n 8387:= 8384:] 8375:T 8371:[ 8367:E 8363:= 8356:] 8351:+ 8347:T 8343:[ 8339:E 8308:T 8285:+ 8281:T 8260:T 8240:n 8217:) 8212:+ 8208:t 8199:+ 8195:T 8191:( 8168:) 8165:n 8157:+ 8153:t 8149:( 8144:1 8138:n 8134:p 8130:+ 8127:) 8122:+ 8118:t 8114:( 8109:1 8103:n 8099:p 8095:= 8092:) 8087:+ 8083:t 8079:( 8074:n 8070:p 8066:2 8046:) 8041:+ 8037:t 8033:( 8028:n 8024:p 8003:n 7981:+ 7977:t 7973:= 7968:+ 7964:T 7943:) 7938:+ 7934:t 7930:( 7925:n 7921:p 7891:n 7887:u 7864:n 7860:2 7855:/ 7851:) 7846:+ 7842:t 7838:( 7833:n 7829:u 7825:= 7822:) 7817:+ 7813:t 7809:= 7804:+ 7800:T 7796:( 7771:+ 7767:T 7746:n 7738:+ 7734:t 7713:} 7710:1 7704:n 7701:, 7695:, 7692:1 7689:{ 7669:n 7649:n 7629:} 7626:1 7620:n 7617:, 7611:, 7608:1 7605:{ 7585:n 7563:+ 7559:t 7538:} 7535:n 7532:, 7526:, 7523:1 7520:{ 7500:. 7497:) 7494:n 7486:+ 7482:t 7478:( 7473:1 7467:n 7463:u 7459:+ 7456:) 7451:+ 7447:t 7443:( 7438:1 7432:n 7428:u 7424:= 7421:) 7416:+ 7412:t 7408:( 7403:n 7399:u 7378:2 7374:/ 7370:) 7367:1 7364:+ 7361:n 7358:( 7355:n 7349:t 7329:0 7323:t 7303:0 7300:= 7297:) 7292:+ 7288:t 7284:( 7279:n 7275:u 7254:0 7246:+ 7242:t 7221:0 7218:= 7215:) 7210:+ 7206:t 7202:( 7197:0 7193:u 7172:1 7169:= 7166:) 7163:0 7160:( 7155:0 7151:u 7128:+ 7124:t 7103:} 7100:n 7097:, 7091:, 7088:1 7085:{ 7063:+ 7059:t 7055:= 7050:+ 7046:T 7025:) 7020:+ 7016:t 7012:( 7007:n 7003:u 6980:+ 6976:T 6955:n 6933:n 6929:2 6908:T 6885:T 6863:n 6859:2 6838:t 6835:= 6832:T 6812:t 6809:= 6806:T 6784:i 6780:X 6759:n 6739:T 6729:p 6717:p 6713:p 6709:p 6691:T 6662:7 6658:2 6653:/ 6646:= 6613:7 6609:2 6604:/ 6597:= 6553:| 6549:T 6545:| 6524:T 6504:T 6484:T 6463:p 6449:} 6446:n 6443:, 6437:, 6434:1 6431:{ 6384:2 6380:/ 6376:) 6370:+ 6367:k 6364:( 6324:k 6304:v 6284:v 6244:v 6224:1 6218:k 6198:v 6178:6 6175:= 6172:3 6168:/ 6164:) 6161:7 6158:+ 6155:6 6152:+ 6149:5 6146:( 6124:7 6120:X 6097:4 6093:X 6070:1 6066:X 6043:6 6039:X 6015:= 6012:2 6008:/ 6004:) 6001:3 5998:+ 5995:2 5992:( 5970:5 5966:X 5943:2 5939:X 5916:3 5912:X 5891:. 5887:| 5881:7 5877:X 5872:| 5868:= 5864:| 5858:4 5854:X 5849:| 5845:= 5841:| 5835:1 5831:X 5826:| 5818:| 5812:6 5808:X 5803:| 5795:| 5789:5 5785:X 5780:| 5776:= 5772:| 5766:2 5762:X 5757:| 5749:| 5743:3 5739:X 5734:| 5710:} 5707:n 5704:, 5698:, 5695:1 5692:{ 5681:n 5654:i 5650:R 5618:2 5615:1 5591:p 5574:j 5554:i 5534:) 5531:0 5523:j 5519:X 5515:+ 5510:i 5506:X 5502:( 5479:) 5476:0 5468:j 5464:X 5460:+ 5455:i 5451:X 5447:( 5424:j 5418:i 5319:0 5316:= 5313:) 5310:0 5307:( 5260:2 5255:/ 5225:2 5220:/ 5164:2 5159:/ 5123:2 5118:/ 5104:p 5070:2 5065:/ 5029:2 5024:/ 5010:p 4962:i 4958:X 4935:j 4931:Y 4922:j 4918:X 4914:= 4909:i 4905:Y 4896:i 4892:X 4869:j 4865:X 4861:= 4856:i 4852:X 4831:j 4825:i 4803:i 4799:Y 4795:= 4790:i 4786:X 4765:) 4760:i 4756:Y 4752:, 4747:i 4743:X 4739:( 4717:i 4713:X 4695:. 4683:) 4680:x 4677:+ 4672:i 4668:Y 4659:i 4655:X 4651:( 4642:) 4639:x 4631:i 4627:Y 4618:i 4614:X 4610:( 4607:r 4604:P 4584:0 4578:x 4556:i 4552:Y 4543:i 4539:X 4526:2 4523:H 4518:. 4506:) 4503:x 4500:+ 4495:i 4491:Y 4482:i 4478:X 4474:( 4465:) 4462:x 4454:i 4450:Y 4441:i 4437:X 4433:( 4430:r 4427:P 4407:0 4401:x 4379:i 4375:Y 4366:i 4362:X 4349:1 4346:H 4329:) 4324:i 4320:Y 4316:, 4311:i 4307:X 4303:( 4291:0 4288:H 4265:i 4261:X 4252:i 4248:Y 4225:i 4221:Y 4212:i 4208:X 4182:) 4171:i 4167:X 4163:, 4157:+ 4152:i 4148:Y 4144:( 4124:) 4119:i 4115:Y 4111:, 4106:i 4102:X 4098:( 4078:0 4060:3 4057:H 4040:) 4029:i 4025:X 4021:, 4015:+ 4010:i 4006:Y 4002:( 3982:) 3977:i 3973:Y 3969:, 3964:i 3960:X 3956:( 3936:0 3918:2 3915:H 3898:) 3887:i 3883:X 3879:, 3873:+ 3868:i 3864:Y 3860:( 3840:) 3835:i 3831:Y 3827:, 3822:i 3818:X 3814:( 3794:0 3776:1 3773:H 3768:. 3756:) 3753:x 3750:, 3747:y 3744:( 3741:F 3738:= 3735:) 3732:y 3729:, 3726:x 3723:( 3720:F 3700:) 3695:i 3691:X 3687:, 3682:i 3678:Y 3674:( 3654:) 3649:i 3645:Y 3641:, 3636:i 3632:X 3628:( 3604:) 3599:i 3595:Y 3591:, 3586:i 3582:X 3578:( 3566:0 3563:H 3553:. 3541:0 3513:i 3509:Y 3500:i 3496:X 3483:3 3480:H 3475:. 3463:0 3435:i 3431:Y 3422:i 3418:X 3405:2 3402:H 3397:. 3385:0 3357:i 3353:Y 3344:i 3340:X 3327:1 3324:H 3319:. 3307:0 3304:= 3279:i 3275:Y 3266:i 3262:X 3249:0 3246:H 3228:) 3223:i 3219:Y 3215:, 3210:i 3206:X 3202:( 3182:) 3179:y 3176:, 3173:x 3170:( 3167:F 3142:i 3138:Y 3129:i 3125:X 3093:0 3066:0 3036:F 3025:2 3022:H 3005:F 2994:1 2991:H 2986:. 2974:0 2971:= 2948:F 2937:0 2934:H 2916:0 2910:x 2890:) 2887:x 2881:X 2878:( 2869:) 2866:x 2857:X 2854:( 2827:F 2807:0 2801:x 2781:) 2778:x 2772:X 2769:( 2760:) 2757:x 2748:X 2745:( 2722:X 2702:F 2678:F 2635:F 2615:F 2575:0 2572:= 2569:) 2563:= 2560:X 2557:( 2542:. 2530:0 2504:F 2493:3 2490:H 2485:. 2473:0 2447:F 2436:2 2433:H 2428:. 2416:0 2390:F 2379:1 2376:H 2371:. 2359:0 2356:= 2333:F 2322:0 2319:H 2301:F 2281:F 2226:. 2223:} 2220:n 2214:j 2208:i 2202:1 2196:0 2188:j 2185:i 2181:W 2177:{ 2171:= 2162:T 2154:, 2151:} 2148:n 2142:j 2136:i 2130:1 2124:0 2116:j 2113:i 2109:W 2105:{ 2099:= 2094:+ 2090:T 2065:) 2060:j 2056:X 2052:+ 2047:i 2043:X 2039:( 2033:2 2030:1 2005:j 2002:i 1998:W 1965:T 1942:+ 1938:T 1917:T 1893:. 1884:T 1880:2 1872:2 1868:) 1865:1 1862:+ 1859:n 1856:( 1853:n 1847:= 1842:2 1838:) 1835:1 1832:+ 1829:n 1826:( 1823:n 1812:+ 1808:T 1804:2 1801:= 1792:T 1783:+ 1779:T 1775:= 1768:T 1761:, 1756:2 1753:T 1743:4 1739:) 1736:1 1733:+ 1730:n 1727:( 1724:n 1718:= 1713:+ 1709:T 1700:2 1696:) 1693:1 1690:+ 1687:n 1684:( 1681:n 1675:= 1662:T 1654:, 1649:2 1646:T 1641:+ 1636:4 1632:) 1629:1 1626:+ 1623:n 1620:( 1617:n 1611:= 1602:T 1593:2 1589:) 1586:1 1583:+ 1580:n 1577:( 1574:n 1568:= 1559:+ 1555:T 1530:2 1526:/ 1522:) 1519:1 1516:+ 1513:n 1510:( 1507:n 1504:= 1501:n 1498:+ 1492:+ 1489:2 1486:+ 1483:1 1457:T 1453:+ 1448:+ 1444:T 1419:. 1414:i 1410:R 1404:0 1396:i 1392:X 1385:, 1382:n 1376:i 1370:1 1362:= 1349:T 1341:, 1336:i 1332:R 1326:0 1318:i 1314:X 1307:, 1304:n 1298:i 1292:1 1284:= 1275:+ 1271:T 1240:T 1214:+ 1210:T 1186:T 1163:i 1143:i 1140:= 1135:) 1132:i 1129:( 1122:R 1100:| 1094:) 1091:n 1088:( 1081:X 1076:| 1062:| 1056:) 1053:1 1050:( 1043:X 1038:| 1017:} 1014:n 1011:, 1005:, 1002:1 999:{ 993:} 990:n 987:, 981:, 978:1 975:{ 972:: 948:| 942:i 938:X 933:| 925:| 919:j 915:X 910:| 889:j 867:i 863:R 838:T 818:p 796:. 791:i 787:R 783:) 778:i 774:X 770:( 759:N 754:1 751:= 748:i 740:= 737:T 717:T 690:0 684:x 664:1 658:= 655:) 652:x 649:( 623:0 617:x 597:1 594:= 591:) 588:x 585:( 530:n 526:R 522:, 516:, 511:1 507:R 485:| 479:n 475:X 470:| 466:, 460:, 456:| 450:1 446:X 441:| 418:. 414:| 408:n 404:X 399:| 395:, 389:, 385:| 379:1 375:X 370:| 343:n 339:X 335:, 329:, 324:1 320:X 290:i 286:Y 277:i 273:X 252:) 247:i 243:Y 239:, 234:i 230:X 226:( 198:) 193:n 189:Y 185:, 180:n 176:X 172:( 169:, 163:, 160:) 155:1 151:Y 147:, 142:1 138:X 134:( 110:T 104:T 67:t 63:t 59:t 49:t 23:.

Index

Wilcoxon rank-sum test
non-parametric
rank test
statistical hypothesis testing
location
Student's t-test
paired difference test
t-test
normal distribution
sign test
Frank Wilcoxon
rank-sum test
Sidney Siegel
interval scale
real numbers
sign function
test statistic
median
mean
pseudomedian
independent and identically distributed
Likert scale
partition function
sign function
absolute value
rank
Mann–Whitney_U_test § Rank-biserial_correlation
effect size
rank-biserial correlation
R

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