3804:
3064:
3799:{\displaystyle {\begin{aligned}{\frac {1}{n^{2}}}\sum _{i,j=1}^{n}(r_{j}-r_{i})(s_{j}-s_{i})&=2\left({\frac {1}{n^{2}}}\cdot n\sum _{i=1}^{n}r_{i}s_{i}-({\frac {1}{n}}\sum _{i=1}^{n}r_{i})({\frac {1}{n}}\sum _{j=1}^{n}s_{j})\right)\\&={\frac {1}{n}}\sum _{i=1}^{n}(r_{i}^{2}+s_{i}^{2}-d_{i}^{2})-2(\mathbb {E} )^{2}\\&={\frac {1}{n}}\sum _{i=1}^{n}r_{i}^{2}+{\frac {1}{n}}\sum _{i=1}^{n}s_{i}^{2}-{\frac {1}{n}}\sum _{i=1}^{n}d_{i}^{2}-2(\mathbb {E} )^{2}\\&=2(\mathbb {E} -(\mathbb {E} )^{2})-{\frac {1}{n}}\sum _{i=1}^{n}d_{i}^{2}\\\end{aligned}}}
7199:
4266:
7185:
4653:
Group A is faster than the runner from Group B. There are a total of 20 pairs, and 19 pairs support the hypothesis. The only pair that does not support the hypothesis are the two runners with ranks 5 and 6, because in this pair, the runner from Group B had the faster time. By the Kerby simple difference formula, 95% of the data support the hypothesis (19 of 20 pairs), and 5% do not support (1 of 20 pairs), so the rank correlation is
7223:
3815:
7211:
4261:{\displaystyle {\begin{aligned}{\frac {1}{n^{2}}}\sum _{i,j=1}^{n}(r_{j}-r_{i})^{2}&={\frac {1}{n^{2}}}\cdot n\sum _{i,j=1}^{n}(r_{i}^{2}+r_{j}^{2}-2r_{i}r_{j})\\&=2{\frac {1}{n}}\sum _{i=1}^{n}r_{i}^{2}-2({\frac {1}{n}}\sum _{i=1}^{n}r_{i})({\frac {1}{n}}\sum _{j=1}^{n}r_{j})\\&=2(\mathbb {E} -(\mathbb {E} )^{2})\\\end{aligned}}}
78:
If, for example, one variable is the identity of a college basketball program and another variable is the identity of a college football program, one could test for a relationship between the poll rankings of the two types of program: do colleges with a higher-ranked basketball program tend to have a
4652:
The analysis is conducted on pairs, defined as a member of one group compared to a member of the other group. For example, the fastest runner in the study is a member of four pairs: (1,5), (1,7), (1,8), and (1,9). All four of these pairs support the hypothesis, because in each pair the runner from
4596:
Kerby showed that this rank correlation can be expressed in terms of two concepts: the percent of data that support a stated hypothesis, and the percent of data that do not support it. The Kerby simple difference formula states that the rank correlation can be expressed as the difference between the
4648:
To illustrate the computation, suppose a coach trains long-distance runners for one month using two methods. Group A has 5 runners, and Group B has 4 runners. The stated hypothesis is that method A produces faster runners. The race to assess the results finds that the runners from Group A do
1891:
82:
If there is only one variable, the identity of a college football program, but it is subject to two different poll rankings (say, one by coaches and one by sportswriters), then the similarity of the two different polls' rankings can be measured with a rank correlation coefficient.
3036:
4452:
919:
79:
higher-ranked football program? A rank correlation coefficient can measure that relationship, and the measure of significance of the rank correlation coefficient can show whether the measured relationship is small enough to likely be a coincidence.
1591:
1176:
2491:
4588:
Dave Kerby (2014) recommended the rank-biserial as the measure to introduce students to rank correlation, because the general logic can be explained at an introductory level. The rank-biserial is the correlation used with the
4668:= 0 indicates that half the pairs favor the hypothesis and half do not; in other words, the sample groups do not differ in ranks, so there is no evidence that they come from two different populations. An effect size of
1801:
1290:
2883:
2878:
4593:, a method commonly covered in introductory college courses on statistics. The data for this test consists of two groups; and for each member of the groups, the outcome is ranked for the study as a whole.
4579:
between two normal variablesâ (p. 91). The rank-biserial correlation had been introduced nine years before by Edward
Cureton (1956) as a measure of rank correlation when the ranks are in two groups.
4277:
50:
variables or different rankings of the same variable, where a "ranking" is the assignment of the ordering labels "first", "second", "third", etc. to different observations of a particular variable. A
2793:
750:
3820:
3069:
2068:
1220:
2184:
2127:
406:
360:
2547:
1082:
1044:
4508:
2631:
1640:
2263:
2225:
1793:
1682:
696:
644:
595:
2695:
1470:
1006:
964:
1725:
3056:
742:
1755:
1090:
546:
496:
4638:
4565:
4531:
2317:
2290:
1953:
1926:
1402:
1375:
251:
231:
2657:
722:
2739:
2715:
2587:
2567:
2357:
2337:
2013:
1993:
1973:
1462:
1442:
1422:
1334:
1314:
516:
466:
446:
426:
314:
294:
274:
2365:
4893:
1886:{\displaystyle \Gamma ={\frac {2\,(({\text{number of concordant pairs}})-({\text{number of discordant pairs}}))}{n(n-1)}}={\text{Kendall's }}\tau }
4694:
6320:
6825:
1229:
138:
6975:
3031:{\displaystyle \mathrm {Var} (U)=\textstyle {\frac {(n+1)(2n+1)}{6}}-\textstyle {\frac {(n+1)(n+1)}{4}}=\textstyle {\frac {n^{2}-1}{12}}}
6599:
5240:
4511:
130:
2798:
4649:
indeed run faster, with the following ranks: 1, 2, 3, 4, and 6. The slower runners from Group B thus have ranks of 5, 7, 8, and 9.
6373:
4447:{\displaystyle \Gamma =1-{\frac {\sum _{i=1}^{n}d_{i}^{2}}{2n\mathrm {Var} (U)}}=1-{\frac {6\sum _{i=1}^{n}d_{i}^{2}}{n(n^{2}-1)}}}
1643:
6812:
914:{\displaystyle \Gamma ={\frac {\sum _{i,j=1}^{n}a_{ij}b_{ij}}{\sqrt {\sum _{i,j=1}^{n}a_{ij}^{2}\sum _{i,j=1}^{n}b_{ij}^{2}}}}}
2744:
5235:
4935:
4575:, the ranking variable, which estimates Spearman's rho between X and Y in the same way that biserial r estimates Pearson's
4542:
7249:
5839:
4987:
17:
4825:
Glass, Gene V. (1965). "A ranking variable analogue of biserial correlation: implications for short-cut item analysis".
1340:
2018:
7254:
6622:
6514:
4855:
4816:
4798:
4738:
2718:
7227:
6800:
6674:
1184:
6858:
6519:
6264:
5635:
5225:
193:
of objects. Thus we can look at observed rankings as data obtained when the sample space is (identified with) a
6909:
6121:
5928:
5817:
5775:
146:
5849:
167:
implies increasing agreement between rankings. The coefficient is inside the interval and assumes the value:
7152:
6111:
5014:
114:âin the column variable), a rank correlation measures the relationship between income and educational level.
6703:
6652:
6637:
6627:
6496:
6368:
6335:
6161:
6116:
5946:
4864:
Kerby, Dave S. (2014). "The Simple
Difference Formula: An Approach to Teaching Nonparametric Correlation".
177:−1 if the disagreement between the two rankings is perfect; one ranking is the reverse of the other.
7215:
7047:
6848:
6772:
6073:
5827:
5496:
4960:
2133:
2076:
365:
319:
4907:
2499:
1049:
1011:
6932:
6904:
6899:
6647:
6406:
6312:
6292:
6200:
5911:
5729:
5212:
5084:
4460:
2592:
1599:
1586:{\displaystyle a_{ij}=\operatorname {sgn}(r_{j}-r_{i}),\quad b_{ij}=\operatorname {sgn}(s_{j}-s_{i}).}
6664:
6432:
6153:
6078:
6007:
5936:
5856:
5844:
5714:
5702:
5695:
5403:
5124:
2230:
2192:
1760:
1649:
1296:. In particular, the general correlation coefficient is the cosine of the angle between the matrices
649:
67:
600:
551:
7147:
6914:
6777:
6462:
6427:
6391:
6176:
5618:
5527:
5486:
5398:
5089:
4928:
2662:
55:
7056:
6669:
6609:
6546:
6184:
6168:
5906:
5768:
5758:
5608:
5522:
4590:
2721:
from discrete mathematics, it is easy to see that for the uniformly distributed random variable,
1223:
63:
969:
927:
7094:
7024:
6817:
6754:
6509:
6396:
5393:
5290:
5197:
5076:
4975:
1171:{\displaystyle \Gamma ={\frac {\langle A,B\rangle _{\rm {F}}}{\|A\|_{\rm {F}}\|B\|_{\rm {F}}}}}
1687:
7119:
7061:
7004:
6830:
6723:
6632:
6358:
6242:
6101:
6093:
5983:
5975:
5790:
5686:
5664:
5623:
5588:
5555:
5501:
5476:
5431:
5370:
5330:
5132:
4955:
4887:
4672:= 0 can be said to describe no relationship between group membership and the members' ranks.
3041:
727:
1730:
521:
471:
7042:
6617:
6566:
6542:
6504:
6422:
6401:
6353:
6232:
6210:
6179:
6088:
5965:
5916:
5834:
5807:
5763:
5719:
5481:
5257:
5137:
4611:
4550:
4516:
2295:
2268:
1931:
1904:
1380:
1353:
236:
216:
198:
8:
7189:
7114:
7037:
6718:
6482:
6475:
6437:
6345:
6325:
6297:
6030:
5896:
5891:
5881:
5873:
5691:
5652:
5542:
5532:
5441:
5220:
5176:
5094:
5019:
4921:
2636:
2486:{\displaystyle \Gamma ={\frac {\sum (r_{j}-r_{i})(s_{j}-s_{i})}{\sum (r_{j}-r_{i})^{2}}}}
701:
7203:
7014:
6868:
6764:
6713:
6589:
6486:
6470:
6447:
6224:
5958:
5941:
5901:
5812:
5707:
5669:
5640:
5600:
5560:
5506:
5423:
5109:
5104:
4838:
4777:
4711:
2724:
2700:
2572:
2552:
2342:
2322:
1998:
1978:
1958:
1447:
1427:
1407:
1319:
1299:
501:
451:
431:
411:
299:
279:
259:
171:
1 if the agreement between the two rankings is perfect; the two rankings are the same.
54:
measures the degree of similarity between two rankings, and can be used to assess the
7259:
7198:
7109:
7079:
7071:
6891:
6882:
6807:
6738:
6594:
6579:
6554:
6442:
6383:
6249:
6237:
5863:
5780:
5724:
5647:
5491:
5413:
5192:
5066:
4851:
4812:
4811:, Lecture Notes-Monograph Series, Hayward, CA: Institute of Mathematical Statistics,
4794:
4781:
4734:
190:
87:
7134:
7089:
6853:
6840:
6733:
6708:
6642:
6574:
6452:
6060:
5953:
5886:
5799:
5746:
5565:
5436:
5114:
5029:
4996:
4873:
4834:
4769:
4703:
276:
objects, which are being considered in relation to two properties, represented by
7051:
6795:
6657:
6584:
6259:
6133:
6106:
6083:
6052:
5679:
5674:
5628:
5358:
5009:
4689:
194:
6541:
4664:= 1, which means that 100% of the pairs favor the hypothesis. A correlation of
7000:
6995:
5458:
5388:
5034:
1293:
4547:
Gene Glass (1965) noted that the rank-biserial can be derived from
Spearman's
548:. The only requirement for these functions is that they be anti-symmetric, so
7243:
7157:
7124:
6987:
6948:
6759:
6728:
6192:
6146:
5751:
5453:
5280:
5044:
5039:
4760:
59:
1642:
is the number of concordant pairs minus the number of discordant pairs (see
7099:
7032:
7009:
6924:
6254:
5550:
5448:
5383:
5325:
5310:
5247:
5202:
202:
154:
47:
7142:
7104:
6787:
6688:
6550:
6363:
6330:
5822:
5739:
5734:
5378:
5335:
5315:
5295:
5285:
5054:
186:
164:
123:
5988:
5468:
5168:
5099:
5049:
5024:
4944:
4773:
4715:
1285:{\displaystyle \|A\|_{\rm {F}}={\sqrt {\langle A,A\rangle _{\rm {F}}}}}
31:
4878:
6141:
5993:
5613:
5408:
5320:
5305:
5300:
5265:
4707:
205:. Different metrics will correspond to different rank correlations.
5657:
5275:
5152:
5147:
5142:
7162:
6863:
253:(rho) are particular cases of a general correlation coefficient.
43:
4910:- Nonparametric effect sizes (Copyright 2015 by Karl L. Weunsch)
2873:{\displaystyle \mathbb {E} =\textstyle {\frac {(n+1)(2n+1)}{6}}}
7084:
6065:
6039:
6019:
5270:
5061:
3038:. Now, observing symmetries allows us to compute the parts of
2697:, we can view both as being random variables distributed like
924:
Equivalently, if all coefficients are collected into matrices
4913:
5004:
62:
methods of significance that use rank correlation are the
4908:
Brief guide by experimental psychologist Karl L. Weunsch
4758:
Cureton, Edward E. (1956). "Rank-biserial correlation".
2788:{\displaystyle \mathbb {E} =\textstyle {\frac {n+1}{2}}}
2589:
be a uniformly distributed discrete random variables on
1341:
Inner product space § Norms on inner product spaces
58:
of the relation between them. For example, two common
2999:
2956:
2910:
2826:
2765:
4614:
4553:
4519:
4463:
4280:
3818:
3067:
3044:
2886:
2801:
2747:
2727:
2703:
2665:
2639:
2595:
2575:
2555:
2502:
2368:
2345:
2325:
2298:
2271:
2233:
2195:
2136:
2079:
2021:
2001:
1981:
1961:
1934:
1907:
1804:
1763:
1733:
1690:
1652:
1602:
1473:
1450:
1430:
1410:
1383:
1356:
1322:
1302:
1232:
1187:
1093:
1052:
1014:
972:
930:
753:
730:
704:
652:
603:
554:
524:
504:
474:
454:
434:
414:
368:
322:
302:
282:
262:
239:
219:
6826:
Autoregressive conditional heteroskedasticity (ARCH)
4543:
MannâWhitney_U_test § Rank-biserial_correlation
2015:-quality respectively, we may consider the matrices
1896:
4809:
1345:
6288:
4632:
4583:
4559:
4525:
4510:is the difference between ranks, which is exactly
4502:
4446:
4260:
3798:
3050:
3030:
2872:
2787:
2733:
2709:
2689:
2651:
2625:
2581:
2561:
2541:
2485:
2351:
2331:
2311:
2284:
2257:
2219:
2178:
2121:
2062:
2007:
1987:
1967:
1947:
1920:
1885:
1787:
1749:
1719:
1676:
1634:
1585:
1456:
1436:
1416:
1396:
1369:
1328:
1308:
1284:
1214:
1170:
1076:
1038:
1000:
958:
913:
736:
716:
690:
638:
589:
540:
510:
490:
460:
440:
420:
400:
354:
308:
288:
268:
245:
225:
208:
7241:
4601:) minus the proportion of unfavorable evidence (
2063:{\displaystyle a,b\in M(n\times n;\mathbb {R} )}
724:.) Then the generalized correlation coefficient
6374:Multivariate adaptive regression splines (MARS)
4695:Journal of the American Statistical Association
4929:
4643:
1215:{\displaystyle \langle A,B\rangle _{\rm {F}}}
174:0 if the rankings are completely independent.
38:is any of several statistics that measure an
4892:: CS1 maint: DOI inactive as of June 2024 (
4567:. "One can derive a coefficient defined on
4536:
2620:
2596:
2549:denote the difference in the ranks for each
1269:
1256:
1240:
1233:
1201:
1188:
1154:
1147:
1136:
1129:
1116:
1103:
383:
369:
337:
323:
4692:(1958). "Ordinal Measures of Association".
117:
4974:
4936:
4922:
4722:
1464:-quality respectively, then we can define
102:in the row variable and educational levelâ
5587:
4877:
4793:, Cambridge: Cambridge University Press,
4660:The maximum value for the correlation is
4228:
4201:
3717:
3690:
3650:
3463:
2803:
2749:
2053:
1817:
1059:
1021:
4806:
1644:Kendall tau rank correlation coefficient
182:
4845:
4788:
4757:
4728:
4688:
4512:Spearman's rank correlation coefficient
14:
7242:
6900:KaplanâMeier estimator (product limit)
4791:The Cambridge Dictionary of Statistics
408:. To any pair of individuals, say the
6973:
6540:
6287:
5586:
5356:
4973:
4917:
4863:
4824:
7210:
6910:Accelerated failure time (AFT) model
201:, making the symmetric group into a
27:Statistic comparing ordinal rankings
7222:
6505:Analysis of variance (ANOVA, anova)
5357:
2179:{\displaystyle b_{ij}:=s_{j}-s_{i}}
2122:{\displaystyle a_{ij}:=r_{j}-r_{i}}
401:{\displaystyle \{y_{i}\}_{i\leq n}}
355:{\displaystyle \{x_{i}\}_{i\leq n}}
24:
6600:CochranâMantelâHaenszel statistics
5226:Pearson product-moment correlation
4839:10.1111/j.1745-3984.1965.tb00396.x
4827:Journal of Educational Measurement
4751:
4597:proportion of favorable evidence (
4347:
4344:
4341:
4281:
3045:
2894:
2891:
2888:
2542:{\displaystyle d_{i}:=r_{i}-s_{i}}
2369:
1805:
1274:
1245:
1206:
1159:
1141:
1121:
1094:
1077:{\displaystyle B^{\textsf {T}}=-B}
1039:{\displaystyle A^{\textsf {T}}=-A}
754:
731:
25:
7271:
4901:
4503:{\displaystyle d_{i}=r_{i}-s_{i}}
2626:{\displaystyle \{1,2,\ldots ,n\}}
2496:To simplify this expression, let
1897:Spearmanâs Ï as a particular case
1635:{\displaystyle \sum a_{ij}b_{ij}}
7221:
7209:
7197:
7184:
7183:
6974:
4571:, the dichotomous variable, and
1346:Kendall's Ï as a particular case
6859:Least-squares spectral analysis
4584:Kerby simple difference formula
2258:{\displaystyle \sum b_{ij}^{2}}
2220:{\displaystyle \sum a_{ij}^{2}}
1788:{\displaystyle \sum b_{ij}^{2}}
1677:{\displaystyle \sum a_{ij}^{2}}
1528:
691:{\displaystyle a_{ij}=b_{ij}=0}
209:General correlation coefficient
163:An increasing rank correlation
5840:Mean-unbiased minimum-variance
4943:
4682:
4438:
4419:
4357:
4351:
4251:
4242:
4238:
4232:
4224:
4218:
4205:
4197:
4181:
4137:
4134:
4090:
4022:
3960:
3894:
3867:
3740:
3731:
3727:
3721:
3713:
3707:
3694:
3686:
3664:
3660:
3654:
3646:
3477:
3473:
3467:
3459:
3450:
3396:
3347:
3303:
3300:
3256:
3171:
3145:
3142:
3116:
2987:
2975:
2972:
2960:
2944:
2929:
2926:
2914:
2904:
2898:
2860:
2845:
2842:
2830:
2820:
2807:
2759:
2753:
2471:
2444:
2436:
2410:
2407:
2381:
2057:
2037:
1866:
1854:
1846:
1843:
1835:
1829:
1821:
1818:
1706:
1694:
1577:
1551:
1522:
1496:
995:
979:
953:
937:
639:{\displaystyle b_{ij}=-b_{ji}}
590:{\displaystyle a_{ij}=-a_{ji}}
122:Some of the more popular rank
13:
1:
7153:Geographic information system
6369:Simultaneous equations models
4675:
2690:{\displaystyle 1,2,\ldots ,n}
316:, forming the sets of values
213:Kendall 1970 showed that his
185:, a ranking can be seen as a
6336:Coefficient of determination
5947:Uniformly most powerful test
52:rank correlation coefficient
7:
6905:Proportional hazards models
6849:Spectral density estimation
6831:Vector autoregression (VAR)
6265:Maximum posterior estimator
5497:Randomized controlled trial
4729:Kendall, Maurice G (1970).
646:. (Note that in particular
42:â the relationship between
10:
7276:
7250:Covariance and correlation
6665:Multivariate distributions
5085:Average absolute deviation
4644:Example and interpretation
4540:
1840:number of discordant pairs
1826:number of concordant pairs
1338:
1001:{\displaystyle B=(b_{ij})}
959:{\displaystyle A=(a_{ij})}
197:. We can then introduce a
73:
7179:
7133:
7070:
7023:
6986:
6982:
6969:
6941:
6923:
6890:
6881:
6839:
6786:
6747:
6696:
6687:
6653:Structural equation model
6608:
6565:
6561:
6536:
6495:
6461:
6415:
6382:
6344:
6311:
6307:
6283:
6223:
6132:
6051:
6015:
6006:
5989:Score/Lagrange multiplier
5974:
5927:
5872:
5798:
5789:
5599:
5595:
5582:
5541:
5515:
5467:
5422:
5404:Sample size determination
5369:
5365:
5352:
5256:
5211:
5185:
5167:
5123:
5075:
4995:
4986:
4982:
4969:
4951:
4657:= .95 − .05 = .90.
4537:Rank-biserial correlation
2659:are just permutations of
1975:-member according to the
1424:-member according to the
256:Suppose we have a set of
86:As another example, in a
68:Wilcoxon signed-rank test
7255:Nonparametric statistics
7148:Environmental statistics
6670:Elliptical distributions
6463:Generalized linear model
6392:Simple linear regression
6162:HodgesâLehmann estimator
5619:Probability distribution
5528:Stochastic approximation
5090:Coefficient of variation
4866:Comprehensive Psychology
4848:Rank Correlation Methods
4731:Rank Correlation Methods
1720:{\displaystyle n(n-1)/2}
118:Correlation coefficients
6808:Cross-correlation (XCF)
6416:Non-standard predictors
5850:LehmannâScheffĂ© theorem
5523:Adaptive clinical trial
4846:Kendall, M. G. (1970),
4789:Everitt, B. S. (2002),
4733:(4 ed.). Griffin.
3051:{\displaystyle \Gamma }
1224:Frobenius inner product
737:{\displaystyle \Gamma }
7204:Mathematics portal
7025:Engineering statistics
6933:NelsonâAalen estimator
6510:Analysis of covariance
6397:Ordinary least squares
6321:Pearson product-moment
5725:Statistical functional
5636:Empirical distribution
5469:Controlled experiments
5198:Frequency distribution
4976:Descriptive statistics
4882:(inactive 2024-06-26).
4634:
4561:
4527:
4504:
4448:
4398:
4316:
4262:
4170:
4123:
4068:
3959:
3866:
3800:
3776:
3624:
3575:
3526:
3395:
3336:
3289:
3232:
3115:
3052:
3032:
2874:
2789:
2735:
2711:
2691:
2653:
2627:
2583:
2563:
2543:
2487:
2353:
2333:
2313:
2286:
2265:are equal, since both
2259:
2221:
2180:
2123:
2064:
2009:
1989:
1969:
1949:
1922:
1887:
1789:
1751:
1750:{\displaystyle a_{ij}}
1727:, the number of terms
1721:
1678:
1636:
1587:
1458:
1438:
1418:
1398:
1371:
1330:
1310:
1286:
1216:
1172:
1078:
1040:
1002:
960:
915:
889:
844:
789:
738:
718:
692:
640:
591:
542:
541:{\displaystyle b_{ij}}
512:
492:
491:{\displaystyle a_{ij}}
462:
442:
422:
402:
356:
310:
290:
270:
247:
227:
147:Goodman and Kruskal's
7120:Population statistics
7062:System identification
6796:Autocorrelation (ACF)
6724:Exponential smoothing
6638:Discriminant analysis
6633:Canonical correlation
6497:Partition of variance
6359:Regression validation
6203:(JonckheereâTerpstra)
6102:Likelihood-ratio test
5791:Frequentist inference
5703:Locationâscale family
5624:Sampling distribution
5589:Statistical inference
5556:Cross-sectional study
5543:Observational studies
5502:Randomized experiment
5331:Stem-and-leaf display
5133:Central limit theorem
4807:Diaconis, P. (1988),
4635:
4633:{\displaystyle r=f-u}
4562:
4560:{\displaystyle \rho }
4528:
4526:{\displaystyle \rho }
4505:
4449:
4378:
4296:
4263:
4150:
4103:
4048:
3933:
3840:
3801:
3756:
3604:
3555:
3506:
3375:
3316:
3269:
3212:
3089:
3053:
3033:
2875:
2790:
2736:
2712:
2692:
2654:
2628:
2584:
2564:
2544:
2488:
2354:
2334:
2314:
2312:{\displaystyle s_{i}}
2287:
2285:{\displaystyle r_{i}}
2260:
2222:
2181:
2124:
2065:
2010:
1990:
1970:
1955:are the ranks of the
1950:
1948:{\displaystyle s_{i}}
1923:
1921:{\displaystyle r_{i}}
1888:
1795:. Thus in this case,
1790:
1752:
1722:
1679:
1637:
1588:
1459:
1439:
1419:
1404:are the ranks of the
1399:
1397:{\displaystyle s_{i}}
1372:
1370:{\displaystyle r_{i}}
1331:
1311:
1287:
1217:
1173:
1079:
1041:
1003:
961:
916:
863:
818:
763:
739:
719:
693:
641:
592:
543:
513:
493:
463:
443:
423:
403:
357:
311:
291:
271:
248:
246:{\displaystyle \rho }
233:(tau) and Spearman's
228:
226:{\displaystyle \tau }
7043:Probabilistic design
6628:Principal components
6471:Exponential families
6423:Nonlinear regression
6402:General linear model
6364:Mixed effects models
6354:Errors and residuals
6331:Confounding variable
6233:Bayesian probability
6211:Van der Waerden test
6201:Ordered alternative
5966:Multiple comparisons
5845:RaoâBlackwellization
5808:Estimating equations
5764:Statistical distance
5482:Factorial experiment
5015:Arithmetic-Geometric
4612:
4551:
4517:
4461:
4278:
3816:
3065:
3042:
2884:
2799:
2745:
2725:
2701:
2663:
2637:
2593:
2573:
2553:
2500:
2366:
2343:
2323:
2296:
2269:
2231:
2193:
2134:
2077:
2019:
1999:
1979:
1959:
1932:
1905:
1802:
1761:
1731:
1688:
1650:
1600:
1471:
1448:
1428:
1408:
1381:
1354:
1320:
1300:
1230:
1185:
1091:
1050:
1012:
970:
928:
751:
728:
702:
650:
601:
552:
522:
502:
472:
452:
432:
412:
366:
320:
300:
280:
260:
237:
217:
7115:Official statistics
7038:Methods engineering
6719:Seasonal adjustment
6487:Poisson regressions
6407:Bayesian regression
6346:Regression analysis
6326:Partial correlation
6298:Regression analysis
5897:Prediction interval
5892:Likelihood interval
5882:Confidence interval
5874:Interval estimation
5835:Unbiased estimators
5653:Model specification
5533:Up-and-down designs
5221:Partial correlation
5177:Index of dispersion
5095:Interquartile range
4850:, London: Griffin,
4690:Kruskal, William H.
4591:MannâWhitney U test
4413:
4331:
4083:
3995:
3977:
3791:
3639:
3590:
3541:
3449:
3431:
3413:
2652:{\displaystyle r,s}
2254:
2216:
1784:
1673:
907:
862:
717:{\displaystyle i=j}
518:-score, denoted by
468:-score, denoted by
126:statistics include
64:MannâWhitney U test
40:ordinal association
18:Ordinal association
7135:Spatial statistics
7015:Medical statistics
6915:First hitting time
6869:Whittle likelihood
6520:Degrees of freedom
6515:Multivariate ANOVA
6448:Heteroscedasticity
6260:Bayesian estimator
6225:Bayesian inference
6074:KolmogorovâSmirnov
5959:Randomization test
5929:Testing hypotheses
5902:Tolerance interval
5813:Maximum likelihood
5708:Exponential family
5641:Density estimation
5601:Statistical theory
5561:Natural experiment
5507:Scientific control
5424:Survey methodology
5110:Standard deviation
4774:10.1007/BF02289138
4630:
4557:
4523:
4500:
4444:
4399:
4317:
4258:
4256:
4069:
3981:
3963:
3796:
3794:
3777:
3625:
3576:
3527:
3435:
3417:
3399:
3048:
3028:
3027:
3026:
3025:
2870:
2869:
2785:
2784:
2731:
2707:
2687:
2649:
2633:. Since the ranks
2623:
2579:
2559:
2539:
2483:
2349:
2329:
2309:
2282:
2255:
2237:
2217:
2199:
2176:
2119:
2060:
2005:
1985:
1965:
1945:
1918:
1883:
1785:
1767:
1747:
1717:
1674:
1656:
1632:
1583:
1454:
1434:
1414:
1394:
1367:
1326:
1306:
1282:
1212:
1168:
1074:
1036:
998:
956:
911:
890:
845:
734:
714:
688:
636:
587:
538:
508:
488:
458:
438:
418:
398:
352:
306:
286:
266:
243:
223:
7237:
7236:
7175:
7174:
7171:
7170:
7110:National accounts
7080:Actuarial science
7072:Social statistics
6965:
6964:
6961:
6960:
6957:
6956:
6892:Survival function
6877:
6876:
6739:Granger causality
6580:Contingency table
6555:Survival analysis
6532:
6531:
6528:
6527:
6384:Linear regression
6279:
6278:
6275:
6274:
6250:Credible interval
6219:
6218:
6002:
6001:
5818:Method of moments
5687:Parametric family
5648:Statistical model
5578:
5577:
5574:
5573:
5492:Random assignment
5414:Statistical power
5348:
5347:
5344:
5343:
5193:Contingency table
5163:
5162:
5030:Generalized/power
4879:10.2466/11.IT.3.1
4442:
4361:
4148:
4101:
4046:
3925:
3838:
3754:
3602:
3553:
3504:
3373:
3314:
3267:
3204:
3087:
3023:
2994:
2951:
2867:
2782:
2734:{\displaystyle U}
2719:summation results
2710:{\displaystyle U}
2582:{\displaystyle U}
2562:{\displaystyle i}
2481:
2352:{\displaystyle n}
2332:{\displaystyle 1}
2008:{\displaystyle y}
1988:{\displaystyle x}
1968:{\displaystyle i}
1878:
1870:
1841:
1827:
1457:{\displaystyle y}
1437:{\displaystyle x}
1417:{\displaystyle i}
1329:{\displaystyle B}
1309:{\displaystyle A}
1280:
1166:
1061:
1023:
909:
908:
511:{\displaystyle y}
461:{\displaystyle x}
441:{\displaystyle j}
421:{\displaystyle i}
309:{\displaystyle y}
289:{\displaystyle x}
269:{\displaystyle n}
88:contingency table
16:(Redirected from
7267:
7225:
7224:
7213:
7212:
7202:
7201:
7187:
7186:
7090:Crime statistics
6984:
6983:
6971:
6970:
6888:
6887:
6854:Fourier analysis
6841:Frequency domain
6821:
6768:
6734:Structural break
6694:
6693:
6643:Cluster analysis
6590:Log-linear model
6563:
6562:
6538:
6537:
6479:
6453:Homoscedasticity
6309:
6308:
6285:
6284:
6204:
6196:
6188:
6187:(KruskalâWallis)
6172:
6157:
6112:Cross validation
6097:
6079:AndersonâDarling
6026:
6013:
6012:
5984:Likelihood-ratio
5976:Parametric tests
5954:Permutation test
5937:1- & 2-tails
5828:Minimum distance
5800:Point estimation
5796:
5795:
5747:Optimal decision
5698:
5597:
5596:
5584:
5583:
5566:Quasi-experiment
5516:Adaptive designs
5367:
5366:
5354:
5353:
5231:Rank correlation
4993:
4992:
4984:
4983:
4971:
4970:
4938:
4931:
4924:
4915:
4914:
4897:
4891:
4883:
4881:
4872:(1): 11.IT.3.1.
4860:
4842:
4821:
4803:
4785:
4745:
4744:
4726:
4720:
4719:
4702:(284): 814â861.
4686:
4639:
4637:
4636:
4631:
4566:
4564:
4563:
4558:
4532:
4530:
4529:
4524:
4509:
4507:
4506:
4501:
4499:
4498:
4486:
4485:
4473:
4472:
4453:
4451:
4450:
4445:
4443:
4441:
4431:
4430:
4414:
4412:
4407:
4397:
4392:
4373:
4362:
4360:
4350:
4332:
4330:
4325:
4315:
4310:
4294:
4267:
4265:
4264:
4259:
4257:
4250:
4249:
4231:
4217:
4216:
4204:
4187:
4180:
4179:
4169:
4164:
4149:
4141:
4133:
4132:
4122:
4117:
4102:
4094:
4082:
4077:
4067:
4062:
4047:
4039:
4028:
4021:
4020:
4011:
4010:
3994:
3989:
3976:
3971:
3958:
3953:
3926:
3924:
3923:
3911:
3902:
3901:
3892:
3891:
3879:
3878:
3865:
3860:
3839:
3837:
3836:
3824:
3805:
3803:
3802:
3797:
3795:
3790:
3785:
3775:
3770:
3755:
3747:
3739:
3738:
3720:
3706:
3705:
3693:
3676:
3672:
3671:
3653:
3638:
3633:
3623:
3618:
3603:
3595:
3589:
3584:
3574:
3569:
3554:
3546:
3540:
3535:
3525:
3520:
3505:
3497:
3489:
3485:
3484:
3466:
3448:
3443:
3430:
3425:
3412:
3407:
3394:
3389:
3374:
3366:
3358:
3354:
3350:
3346:
3345:
3335:
3330:
3315:
3307:
3299:
3298:
3288:
3283:
3268:
3260:
3252:
3251:
3242:
3241:
3231:
3226:
3205:
3203:
3202:
3190:
3170:
3169:
3157:
3156:
3141:
3140:
3128:
3127:
3114:
3109:
3088:
3086:
3085:
3073:
3057:
3055:
3054:
3049:
3037:
3035:
3034:
3029:
3024:
3019:
3012:
3011:
3001:
2995:
2990:
2958:
2952:
2947:
2912:
2897:
2879:
2877:
2876:
2871:
2868:
2863:
2828:
2819:
2818:
2806:
2794:
2792:
2791:
2786:
2783:
2778:
2767:
2752:
2740:
2738:
2737:
2732:
2716:
2714:
2713:
2708:
2696:
2694:
2693:
2688:
2658:
2656:
2655:
2650:
2632:
2630:
2629:
2624:
2588:
2586:
2585:
2580:
2568:
2566:
2565:
2560:
2548:
2546:
2545:
2540:
2538:
2537:
2525:
2524:
2512:
2511:
2492:
2490:
2489:
2484:
2482:
2480:
2479:
2478:
2469:
2468:
2456:
2455:
2439:
2435:
2434:
2422:
2421:
2406:
2405:
2393:
2392:
2376:
2358:
2356:
2355:
2350:
2338:
2336:
2335:
2330:
2318:
2316:
2315:
2310:
2308:
2307:
2291:
2289:
2288:
2283:
2281:
2280:
2264:
2262:
2261:
2256:
2253:
2248:
2226:
2224:
2223:
2218:
2215:
2210:
2185:
2183:
2182:
2177:
2175:
2174:
2162:
2161:
2149:
2148:
2128:
2126:
2125:
2120:
2118:
2117:
2105:
2104:
2092:
2091:
2069:
2067:
2066:
2061:
2056:
2014:
2012:
2011:
2006:
1994:
1992:
1991:
1986:
1974:
1972:
1971:
1966:
1954:
1952:
1951:
1946:
1944:
1943:
1927:
1925:
1924:
1919:
1917:
1916:
1892:
1890:
1889:
1884:
1879:
1876:
1871:
1869:
1849:
1842:
1839:
1828:
1825:
1812:
1794:
1792:
1791:
1786:
1783:
1778:
1756:
1754:
1753:
1748:
1746:
1745:
1726:
1724:
1723:
1718:
1713:
1683:
1681:
1680:
1675:
1672:
1667:
1641:
1639:
1638:
1633:
1631:
1630:
1618:
1617:
1592:
1590:
1589:
1584:
1576:
1575:
1563:
1562:
1541:
1540:
1521:
1520:
1508:
1507:
1486:
1485:
1463:
1461:
1460:
1455:
1443:
1441:
1440:
1435:
1423:
1421:
1420:
1415:
1403:
1401:
1400:
1395:
1393:
1392:
1376:
1374:
1373:
1368:
1366:
1365:
1335:
1333:
1332:
1327:
1315:
1313:
1312:
1307:
1291:
1289:
1288:
1283:
1281:
1279:
1278:
1277:
1255:
1250:
1249:
1248:
1221:
1219:
1218:
1213:
1211:
1210:
1209:
1177:
1175:
1174:
1169:
1167:
1165:
1164:
1163:
1162:
1146:
1145:
1144:
1127:
1126:
1125:
1124:
1101:
1083:
1081:
1080:
1075:
1064:
1063:
1062:
1045:
1043:
1042:
1037:
1026:
1025:
1024:
1007:
1005:
1004:
999:
994:
993:
965:
963:
962:
957:
952:
951:
920:
918:
917:
912:
910:
906:
901:
888:
883:
861:
856:
843:
838:
817:
816:
815:
814:
802:
801:
788:
783:
761:
743:
741:
740:
735:
723:
721:
720:
715:
697:
695:
694:
689:
681:
680:
665:
664:
645:
643:
642:
637:
635:
634:
616:
615:
596:
594:
593:
588:
586:
585:
567:
566:
547:
545:
544:
539:
537:
536:
517:
515:
514:
509:
497:
495:
494:
489:
487:
486:
467:
465:
464:
459:
448:-th we assign a
447:
445:
444:
439:
427:
425:
424:
419:
407:
405:
404:
399:
397:
396:
381:
380:
361:
359:
358:
353:
351:
350:
335:
334:
315:
313:
312:
307:
295:
293:
292:
287:
275:
273:
272:
267:
252:
250:
249:
244:
232:
230:
229:
224:
36:rank correlation
21:
7275:
7274:
7270:
7269:
7268:
7266:
7265:
7264:
7240:
7239:
7238:
7233:
7196:
7167:
7129:
7066:
7052:quality control
7019:
7001:Clinical trials
6978:
6953:
6937:
6925:Hazard function
6919:
6873:
6835:
6819:
6782:
6778:BreuschâGodfrey
6766:
6743:
6683:
6658:Factor analysis
6604:
6585:Graphical model
6557:
6524:
6491:
6477:
6457:
6411:
6378:
6340:
6303:
6302:
6271:
6215:
6202:
6194:
6186:
6170:
6155:
6134:Rank statistics
6128:
6107:Model selection
6095:
6053:Goodness of fit
6047:
6024:
5998:
5970:
5923:
5868:
5857:Median unbiased
5785:
5696:
5629:Order statistic
5591:
5570:
5537:
5511:
5463:
5418:
5361:
5359:Data collection
5340:
5252:
5207:
5181:
5159:
5119:
5071:
4988:Continuous data
4978:
4965:
4947:
4942:
4904:
4885:
4884:
4858:
4819:
4801:
4754:
4752:Further reading
4749:
4748:
4741:
4727:
4723:
4708:10.2307/2281954
4687:
4683:
4678:
4646:
4613:
4610:
4609:
4586:
4552:
4549:
4548:
4545:
4539:
4518:
4515:
4514:
4494:
4490:
4481:
4477:
4468:
4464:
4462:
4459:
4458:
4426:
4422:
4415:
4408:
4403:
4393:
4382:
4374:
4372:
4340:
4333:
4326:
4321:
4311:
4300:
4295:
4293:
4279:
4276:
4275:
4255:
4254:
4245:
4241:
4227:
4212:
4208:
4200:
4185:
4184:
4175:
4171:
4165:
4154:
4140:
4128:
4124:
4118:
4107:
4093:
4078:
4073:
4063:
4052:
4038:
4026:
4025:
4016:
4012:
4006:
4002:
3990:
3985:
3972:
3967:
3954:
3937:
3919:
3915:
3910:
3903:
3897:
3893:
3887:
3883:
3874:
3870:
3861:
3844:
3832:
3828:
3823:
3819:
3817:
3814:
3813:
3793:
3792:
3786:
3781:
3771:
3760:
3746:
3734:
3730:
3716:
3701:
3697:
3689:
3674:
3673:
3667:
3663:
3649:
3634:
3629:
3619:
3608:
3594:
3585:
3580:
3570:
3559:
3545:
3536:
3531:
3521:
3510:
3496:
3487:
3486:
3480:
3476:
3462:
3444:
3439:
3426:
3421:
3408:
3403:
3390:
3379:
3365:
3356:
3355:
3341:
3337:
3331:
3320:
3306:
3294:
3290:
3284:
3273:
3259:
3247:
3243:
3237:
3233:
3227:
3216:
3198:
3194:
3189:
3188:
3184:
3174:
3165:
3161:
3152:
3148:
3136:
3132:
3123:
3119:
3110:
3093:
3081:
3077:
3072:
3068:
3066:
3063:
3062:
3043:
3040:
3039:
3007:
3003:
3002:
3000:
2959:
2957:
2913:
2911:
2887:
2885:
2882:
2881:
2829:
2827:
2814:
2810:
2802:
2800:
2797:
2796:
2768:
2766:
2748:
2746:
2743:
2742:
2726:
2723:
2722:
2702:
2699:
2698:
2664:
2661:
2660:
2638:
2635:
2634:
2594:
2591:
2590:
2574:
2571:
2570:
2569:. Further, let
2554:
2551:
2550:
2533:
2529:
2520:
2516:
2507:
2503:
2501:
2498:
2497:
2474:
2470:
2464:
2460:
2451:
2447:
2440:
2430:
2426:
2417:
2413:
2401:
2397:
2388:
2384:
2377:
2375:
2367:
2364:
2363:
2344:
2341:
2340:
2324:
2321:
2320:
2303:
2299:
2297:
2294:
2293:
2276:
2272:
2270:
2267:
2266:
2249:
2241:
2232:
2229:
2228:
2211:
2203:
2194:
2191:
2190:
2170:
2166:
2157:
2153:
2141:
2137:
2135:
2132:
2131:
2113:
2109:
2100:
2096:
2084:
2080:
2078:
2075:
2074:
2052:
2020:
2017:
2016:
2000:
1997:
1996:
1980:
1977:
1976:
1960:
1957:
1956:
1939:
1935:
1933:
1930:
1929:
1912:
1908:
1906:
1903:
1902:
1899:
1877:Kendall's
1875:
1850:
1838:
1824:
1813:
1811:
1803:
1800:
1799:
1779:
1771:
1762:
1759:
1758:
1738:
1734:
1732:
1729:
1728:
1709:
1689:
1686:
1685:
1668:
1660:
1651:
1648:
1647:
1623:
1619:
1610:
1606:
1601:
1598:
1597:
1571:
1567:
1558:
1554:
1533:
1529:
1516:
1512:
1503:
1499:
1478:
1474:
1472:
1469:
1468:
1449:
1446:
1445:
1429:
1426:
1425:
1409:
1406:
1405:
1388:
1384:
1382:
1379:
1378:
1361:
1357:
1355:
1352:
1351:
1348:
1343:
1321:
1318:
1317:
1301:
1298:
1297:
1273:
1272:
1268:
1254:
1244:
1243:
1239:
1231:
1228:
1227:
1205:
1204:
1200:
1186:
1183:
1182:
1158:
1157:
1153:
1140:
1139:
1135:
1128:
1120:
1119:
1115:
1102:
1100:
1092:
1089:
1088:
1058:
1057:
1053:
1051:
1048:
1047:
1020:
1019:
1015:
1013:
1010:
1009:
986:
982:
971:
968:
967:
944:
940:
929:
926:
925:
902:
894:
884:
867:
857:
849:
839:
822:
807:
803:
794:
790:
784:
767:
762:
760:
752:
749:
748:
729:
726:
725:
703:
700:
699:
673:
669:
657:
653:
651:
648:
647:
627:
623:
608:
604:
602:
599:
598:
578:
574:
559:
555:
553:
550:
549:
529:
525:
523:
520:
519:
503:
500:
499:
479:
475:
473:
470:
469:
453:
450:
449:
433:
430:
429:
413:
410:
409:
386:
382:
376:
372:
367:
364:
363:
340:
336:
330:
326:
321:
318:
317:
301:
298:
297:
281:
278:
277:
261:
258:
257:
238:
235:
234:
218:
215:
214:
211:
195:symmetric group
183:Diaconis (1988)
120:
76:
28:
23:
22:
15:
12:
11:
5:
7273:
7263:
7262:
7257:
7252:
7235:
7234:
7232:
7231:
7219:
7207:
7193:
7180:
7177:
7176:
7173:
7172:
7169:
7168:
7166:
7165:
7160:
7155:
7150:
7145:
7139:
7137:
7131:
7130:
7128:
7127:
7122:
7117:
7112:
7107:
7102:
7097:
7092:
7087:
7082:
7076:
7074:
7068:
7067:
7065:
7064:
7059:
7054:
7045:
7040:
7035:
7029:
7027:
7021:
7020:
7018:
7017:
7012:
7007:
6998:
6996:Bioinformatics
6992:
6990:
6980:
6979:
6967:
6966:
6963:
6962:
6959:
6958:
6955:
6954:
6952:
6951:
6945:
6943:
6939:
6938:
6936:
6935:
6929:
6927:
6921:
6920:
6918:
6917:
6912:
6907:
6902:
6896:
6894:
6885:
6879:
6878:
6875:
6874:
6872:
6871:
6866:
6861:
6856:
6851:
6845:
6843:
6837:
6836:
6834:
6833:
6828:
6823:
6815:
6810:
6805:
6804:
6803:
6801:partial (PACF)
6792:
6790:
6784:
6783:
6781:
6780:
6775:
6770:
6762:
6757:
6751:
6749:
6748:Specific tests
6745:
6744:
6742:
6741:
6736:
6731:
6726:
6721:
6716:
6711:
6706:
6700:
6698:
6691:
6685:
6684:
6682:
6681:
6680:
6679:
6678:
6677:
6662:
6661:
6660:
6650:
6648:Classification
6645:
6640:
6635:
6630:
6625:
6620:
6614:
6612:
6606:
6605:
6603:
6602:
6597:
6595:McNemar's test
6592:
6587:
6582:
6577:
6571:
6569:
6559:
6558:
6534:
6533:
6530:
6529:
6526:
6525:
6523:
6522:
6517:
6512:
6507:
6501:
6499:
6493:
6492:
6490:
6489:
6473:
6467:
6465:
6459:
6458:
6456:
6455:
6450:
6445:
6440:
6435:
6433:Semiparametric
6430:
6425:
6419:
6417:
6413:
6412:
6410:
6409:
6404:
6399:
6394:
6388:
6386:
6380:
6379:
6377:
6376:
6371:
6366:
6361:
6356:
6350:
6348:
6342:
6341:
6339:
6338:
6333:
6328:
6323:
6317:
6315:
6305:
6304:
6301:
6300:
6295:
6289:
6281:
6280:
6277:
6276:
6273:
6272:
6270:
6269:
6268:
6267:
6257:
6252:
6247:
6246:
6245:
6240:
6229:
6227:
6221:
6220:
6217:
6216:
6214:
6213:
6208:
6207:
6206:
6198:
6190:
6174:
6171:(MannâWhitney)
6166:
6165:
6164:
6151:
6150:
6149:
6138:
6136:
6130:
6129:
6127:
6126:
6125:
6124:
6119:
6114:
6104:
6099:
6096:(ShapiroâWilk)
6091:
6086:
6081:
6076:
6071:
6063:
6057:
6055:
6049:
6048:
6046:
6045:
6037:
6028:
6016:
6010:
6008:Specific tests
6004:
6003:
6000:
5999:
5997:
5996:
5991:
5986:
5980:
5978:
5972:
5971:
5969:
5968:
5963:
5962:
5961:
5951:
5950:
5949:
5939:
5933:
5931:
5925:
5924:
5922:
5921:
5920:
5919:
5914:
5904:
5899:
5894:
5889:
5884:
5878:
5876:
5870:
5869:
5867:
5866:
5861:
5860:
5859:
5854:
5853:
5852:
5847:
5832:
5831:
5830:
5825:
5820:
5815:
5804:
5802:
5793:
5787:
5786:
5784:
5783:
5778:
5773:
5772:
5771:
5761:
5756:
5755:
5754:
5744:
5743:
5742:
5737:
5732:
5722:
5717:
5712:
5711:
5710:
5705:
5700:
5684:
5683:
5682:
5677:
5672:
5662:
5661:
5660:
5655:
5645:
5644:
5643:
5633:
5632:
5631:
5621:
5616:
5611:
5605:
5603:
5593:
5592:
5580:
5579:
5576:
5575:
5572:
5571:
5569:
5568:
5563:
5558:
5553:
5547:
5545:
5539:
5538:
5536:
5535:
5530:
5525:
5519:
5517:
5513:
5512:
5510:
5509:
5504:
5499:
5494:
5489:
5484:
5479:
5473:
5471:
5465:
5464:
5462:
5461:
5459:Standard error
5456:
5451:
5446:
5445:
5444:
5439:
5428:
5426:
5420:
5419:
5417:
5416:
5411:
5406:
5401:
5396:
5391:
5389:Optimal design
5386:
5381:
5375:
5373:
5363:
5362:
5350:
5349:
5346:
5345:
5342:
5341:
5339:
5338:
5333:
5328:
5323:
5318:
5313:
5308:
5303:
5298:
5293:
5288:
5283:
5278:
5273:
5268:
5262:
5260:
5254:
5253:
5251:
5250:
5245:
5244:
5243:
5238:
5228:
5223:
5217:
5215:
5209:
5208:
5206:
5205:
5200:
5195:
5189:
5187:
5186:Summary tables
5183:
5182:
5180:
5179:
5173:
5171:
5165:
5164:
5161:
5160:
5158:
5157:
5156:
5155:
5150:
5145:
5135:
5129:
5127:
5121:
5120:
5118:
5117:
5112:
5107:
5102:
5097:
5092:
5087:
5081:
5079:
5073:
5072:
5070:
5069:
5064:
5059:
5058:
5057:
5052:
5047:
5042:
5037:
5032:
5027:
5022:
5020:Contraharmonic
5017:
5012:
5001:
4999:
4990:
4980:
4979:
4967:
4966:
4964:
4963:
4958:
4952:
4949:
4948:
4941:
4940:
4933:
4926:
4918:
4912:
4911:
4903:
4902:External links
4900:
4899:
4898:
4861:
4856:
4843:
4822:
4817:
4804:
4799:
4786:
4768:(3): 287â290.
4753:
4750:
4747:
4746:
4739:
4721:
4680:
4679:
4677:
4674:
4645:
4642:
4641:
4640:
4629:
4626:
4623:
4620:
4617:
4585:
4582:
4556:
4541:Main article:
4538:
4535:
4522:
4497:
4493:
4489:
4484:
4480:
4476:
4471:
4467:
4455:
4454:
4440:
4437:
4434:
4429:
4425:
4421:
4418:
4411:
4406:
4402:
4396:
4391:
4388:
4385:
4381:
4377:
4371:
4368:
4365:
4359:
4356:
4353:
4349:
4346:
4343:
4339:
4336:
4329:
4324:
4320:
4314:
4309:
4306:
4303:
4299:
4292:
4289:
4286:
4283:
4269:
4268:
4253:
4248:
4244:
4240:
4237:
4234:
4230:
4226:
4223:
4220:
4215:
4211:
4207:
4203:
4199:
4196:
4193:
4190:
4188:
4186:
4183:
4178:
4174:
4168:
4163:
4160:
4157:
4153:
4147:
4144:
4139:
4136:
4131:
4127:
4121:
4116:
4113:
4110:
4106:
4100:
4097:
4092:
4089:
4086:
4081:
4076:
4072:
4066:
4061:
4058:
4055:
4051:
4045:
4042:
4037:
4034:
4031:
4029:
4027:
4024:
4019:
4015:
4009:
4005:
4001:
3998:
3993:
3988:
3984:
3980:
3975:
3970:
3966:
3962:
3957:
3952:
3949:
3946:
3943:
3940:
3936:
3932:
3929:
3922:
3918:
3914:
3909:
3906:
3904:
3900:
3896:
3890:
3886:
3882:
3877:
3873:
3869:
3864:
3859:
3856:
3853:
3850:
3847:
3843:
3835:
3831:
3827:
3822:
3821:
3807:
3806:
3789:
3784:
3780:
3774:
3769:
3766:
3763:
3759:
3753:
3750:
3745:
3742:
3737:
3733:
3729:
3726:
3723:
3719:
3715:
3712:
3709:
3704:
3700:
3696:
3692:
3688:
3685:
3682:
3679:
3677:
3675:
3670:
3666:
3662:
3659:
3656:
3652:
3648:
3645:
3642:
3637:
3632:
3628:
3622:
3617:
3614:
3611:
3607:
3601:
3598:
3593:
3588:
3583:
3579:
3573:
3568:
3565:
3562:
3558:
3552:
3549:
3544:
3539:
3534:
3530:
3524:
3519:
3516:
3513:
3509:
3503:
3500:
3495:
3492:
3490:
3488:
3483:
3479:
3475:
3472:
3469:
3465:
3461:
3458:
3455:
3452:
3447:
3442:
3438:
3434:
3429:
3424:
3420:
3416:
3411:
3406:
3402:
3398:
3393:
3388:
3385:
3382:
3378:
3372:
3369:
3364:
3361:
3359:
3357:
3353:
3349:
3344:
3340:
3334:
3329:
3326:
3323:
3319:
3313:
3310:
3305:
3302:
3297:
3293:
3287:
3282:
3279:
3276:
3272:
3266:
3263:
3258:
3255:
3250:
3246:
3240:
3236:
3230:
3225:
3222:
3219:
3215:
3211:
3208:
3201:
3197:
3193:
3187:
3183:
3180:
3177:
3175:
3173:
3168:
3164:
3160:
3155:
3151:
3147:
3144:
3139:
3135:
3131:
3126:
3122:
3118:
3113:
3108:
3105:
3102:
3099:
3096:
3092:
3084:
3080:
3076:
3071:
3070:
3047:
3022:
3018:
3015:
3010:
3006:
2998:
2993:
2989:
2986:
2983:
2980:
2977:
2974:
2971:
2968:
2965:
2962:
2955:
2950:
2946:
2943:
2940:
2937:
2934:
2931:
2928:
2925:
2922:
2919:
2916:
2909:
2906:
2903:
2900:
2896:
2893:
2890:
2866:
2862:
2859:
2856:
2853:
2850:
2847:
2844:
2841:
2838:
2835:
2832:
2825:
2822:
2817:
2813:
2809:
2805:
2781:
2777:
2774:
2771:
2764:
2761:
2758:
2755:
2751:
2730:
2717:. Using basic
2706:
2686:
2683:
2680:
2677:
2674:
2671:
2668:
2648:
2645:
2642:
2622:
2619:
2616:
2613:
2610:
2607:
2604:
2601:
2598:
2578:
2558:
2536:
2532:
2528:
2523:
2519:
2515:
2510:
2506:
2494:
2493:
2477:
2473:
2467:
2463:
2459:
2454:
2450:
2446:
2443:
2438:
2433:
2429:
2425:
2420:
2416:
2412:
2409:
2404:
2400:
2396:
2391:
2387:
2383:
2380:
2374:
2371:
2348:
2328:
2306:
2302:
2279:
2275:
2252:
2247:
2244:
2240:
2236:
2214:
2209:
2206:
2202:
2198:
2187:
2186:
2173:
2169:
2165:
2160:
2156:
2152:
2147:
2144:
2140:
2129:
2116:
2112:
2108:
2103:
2099:
2095:
2090:
2087:
2083:
2059:
2055:
2051:
2048:
2045:
2042:
2039:
2036:
2033:
2030:
2027:
2024:
2004:
1984:
1964:
1942:
1938:
1915:
1911:
1898:
1895:
1894:
1893:
1882:
1874:
1868:
1865:
1862:
1859:
1856:
1853:
1848:
1845:
1837:
1834:
1831:
1823:
1820:
1816:
1810:
1807:
1782:
1777:
1774:
1770:
1766:
1744:
1741:
1737:
1716:
1712:
1708:
1705:
1702:
1699:
1696:
1693:
1671:
1666:
1663:
1659:
1655:
1629:
1626:
1622:
1616:
1613:
1609:
1605:
1594:
1593:
1582:
1579:
1574:
1570:
1566:
1561:
1557:
1553:
1550:
1547:
1544:
1539:
1536:
1532:
1527:
1524:
1519:
1515:
1511:
1506:
1502:
1498:
1495:
1492:
1489:
1484:
1481:
1477:
1453:
1433:
1413:
1391:
1387:
1364:
1360:
1347:
1344:
1325:
1305:
1294:Frobenius norm
1276:
1271:
1267:
1264:
1261:
1258:
1253:
1247:
1242:
1238:
1235:
1208:
1203:
1199:
1196:
1193:
1190:
1179:
1178:
1161:
1156:
1152:
1149:
1143:
1138:
1134:
1131:
1123:
1118:
1114:
1111:
1108:
1105:
1099:
1096:
1073:
1070:
1067:
1056:
1035:
1032:
1029:
1018:
997:
992:
989:
985:
981:
978:
975:
955:
950:
947:
943:
939:
936:
933:
922:
921:
905:
900:
897:
893:
887:
882:
879:
876:
873:
870:
866:
860:
855:
852:
848:
842:
837:
834:
831:
828:
825:
821:
813:
810:
806:
800:
797:
793:
787:
782:
779:
776:
773:
770:
766:
759:
756:
744:is defined as
733:
713:
710:
707:
687:
684:
679:
676:
672:
668:
663:
660:
656:
633:
630:
626:
622:
619:
614:
611:
607:
584:
581:
577:
573:
570:
565:
562:
558:
535:
532:
528:
507:
485:
482:
478:
457:
437:
417:
395:
392:
389:
385:
379:
375:
371:
349:
346:
343:
339:
333:
329:
325:
305:
285:
265:
242:
222:
210:
207:
179:
178:
175:
172:
161:
160:
152:
144:
136:
119:
116:
104:no high school
75:
72:
26:
9:
6:
4:
3:
2:
7272:
7261:
7258:
7256:
7253:
7251:
7248:
7247:
7245:
7230:
7229:
7220:
7218:
7217:
7208:
7206:
7205:
7200:
7194:
7192:
7191:
7182:
7181:
7178:
7164:
7161:
7159:
7158:Geostatistics
7156:
7154:
7151:
7149:
7146:
7144:
7141:
7140:
7138:
7136:
7132:
7126:
7125:Psychometrics
7123:
7121:
7118:
7116:
7113:
7111:
7108:
7106:
7103:
7101:
7098:
7096:
7093:
7091:
7088:
7086:
7083:
7081:
7078:
7077:
7075:
7073:
7069:
7063:
7060:
7058:
7055:
7053:
7049:
7046:
7044:
7041:
7039:
7036:
7034:
7031:
7030:
7028:
7026:
7022:
7016:
7013:
7011:
7008:
7006:
7002:
6999:
6997:
6994:
6993:
6991:
6989:
6988:Biostatistics
6985:
6981:
6977:
6972:
6968:
6950:
6949:Log-rank test
6947:
6946:
6944:
6940:
6934:
6931:
6930:
6928:
6926:
6922:
6916:
6913:
6911:
6908:
6906:
6903:
6901:
6898:
6897:
6895:
6893:
6889:
6886:
6884:
6880:
6870:
6867:
6865:
6862:
6860:
6857:
6855:
6852:
6850:
6847:
6846:
6844:
6842:
6838:
6832:
6829:
6827:
6824:
6822:
6820:(BoxâJenkins)
6816:
6814:
6811:
6809:
6806:
6802:
6799:
6798:
6797:
6794:
6793:
6791:
6789:
6785:
6779:
6776:
6774:
6773:DurbinâWatson
6771:
6769:
6763:
6761:
6758:
6756:
6755:DickeyâFuller
6753:
6752:
6750:
6746:
6740:
6737:
6735:
6732:
6730:
6729:Cointegration
6727:
6725:
6722:
6720:
6717:
6715:
6712:
6710:
6707:
6705:
6704:Decomposition
6702:
6701:
6699:
6695:
6692:
6690:
6686:
6676:
6673:
6672:
6671:
6668:
6667:
6666:
6663:
6659:
6656:
6655:
6654:
6651:
6649:
6646:
6644:
6641:
6639:
6636:
6634:
6631:
6629:
6626:
6624:
6621:
6619:
6616:
6615:
6613:
6611:
6607:
6601:
6598:
6596:
6593:
6591:
6588:
6586:
6583:
6581:
6578:
6576:
6575:Cohen's kappa
6573:
6572:
6570:
6568:
6564:
6560:
6556:
6552:
6548:
6544:
6539:
6535:
6521:
6518:
6516:
6513:
6511:
6508:
6506:
6503:
6502:
6500:
6498:
6494:
6488:
6484:
6480:
6474:
6472:
6469:
6468:
6466:
6464:
6460:
6454:
6451:
6449:
6446:
6444:
6441:
6439:
6436:
6434:
6431:
6429:
6428:Nonparametric
6426:
6424:
6421:
6420:
6418:
6414:
6408:
6405:
6403:
6400:
6398:
6395:
6393:
6390:
6389:
6387:
6385:
6381:
6375:
6372:
6370:
6367:
6365:
6362:
6360:
6357:
6355:
6352:
6351:
6349:
6347:
6343:
6337:
6334:
6332:
6329:
6327:
6324:
6322:
6319:
6318:
6316:
6314:
6310:
6306:
6299:
6296:
6294:
6291:
6290:
6286:
6282:
6266:
6263:
6262:
6261:
6258:
6256:
6253:
6251:
6248:
6244:
6241:
6239:
6236:
6235:
6234:
6231:
6230:
6228:
6226:
6222:
6212:
6209:
6205:
6199:
6197:
6191:
6189:
6183:
6182:
6181:
6178:
6177:Nonparametric
6175:
6173:
6167:
6163:
6160:
6159:
6158:
6152:
6148:
6147:Sample median
6145:
6144:
6143:
6140:
6139:
6137:
6135:
6131:
6123:
6120:
6118:
6115:
6113:
6110:
6109:
6108:
6105:
6103:
6100:
6098:
6092:
6090:
6087:
6085:
6082:
6080:
6077:
6075:
6072:
6070:
6068:
6064:
6062:
6059:
6058:
6056:
6054:
6050:
6044:
6042:
6038:
6036:
6034:
6029:
6027:
6022:
6018:
6017:
6014:
6011:
6009:
6005:
5995:
5992:
5990:
5987:
5985:
5982:
5981:
5979:
5977:
5973:
5967:
5964:
5960:
5957:
5956:
5955:
5952:
5948:
5945:
5944:
5943:
5940:
5938:
5935:
5934:
5932:
5930:
5926:
5918:
5915:
5913:
5910:
5909:
5908:
5905:
5903:
5900:
5898:
5895:
5893:
5890:
5888:
5885:
5883:
5880:
5879:
5877:
5875:
5871:
5865:
5862:
5858:
5855:
5851:
5848:
5846:
5843:
5842:
5841:
5838:
5837:
5836:
5833:
5829:
5826:
5824:
5821:
5819:
5816:
5814:
5811:
5810:
5809:
5806:
5805:
5803:
5801:
5797:
5794:
5792:
5788:
5782:
5779:
5777:
5774:
5770:
5767:
5766:
5765:
5762:
5760:
5757:
5753:
5752:loss function
5750:
5749:
5748:
5745:
5741:
5738:
5736:
5733:
5731:
5728:
5727:
5726:
5723:
5721:
5718:
5716:
5713:
5709:
5706:
5704:
5701:
5699:
5693:
5690:
5689:
5688:
5685:
5681:
5678:
5676:
5673:
5671:
5668:
5667:
5666:
5663:
5659:
5656:
5654:
5651:
5650:
5649:
5646:
5642:
5639:
5638:
5637:
5634:
5630:
5627:
5626:
5625:
5622:
5620:
5617:
5615:
5612:
5610:
5607:
5606:
5604:
5602:
5598:
5594:
5590:
5585:
5581:
5567:
5564:
5562:
5559:
5557:
5554:
5552:
5549:
5548:
5546:
5544:
5540:
5534:
5531:
5529:
5526:
5524:
5521:
5520:
5518:
5514:
5508:
5505:
5503:
5500:
5498:
5495:
5493:
5490:
5488:
5485:
5483:
5480:
5478:
5475:
5474:
5472:
5470:
5466:
5460:
5457:
5455:
5454:Questionnaire
5452:
5450:
5447:
5443:
5440:
5438:
5435:
5434:
5433:
5430:
5429:
5427:
5425:
5421:
5415:
5412:
5410:
5407:
5405:
5402:
5400:
5397:
5395:
5392:
5390:
5387:
5385:
5382:
5380:
5377:
5376:
5374:
5372:
5368:
5364:
5360:
5355:
5351:
5337:
5334:
5332:
5329:
5327:
5324:
5322:
5319:
5317:
5314:
5312:
5309:
5307:
5304:
5302:
5299:
5297:
5294:
5292:
5289:
5287:
5284:
5282:
5281:Control chart
5279:
5277:
5274:
5272:
5269:
5267:
5264:
5263:
5261:
5259:
5255:
5249:
5246:
5242:
5239:
5237:
5234:
5233:
5232:
5229:
5227:
5224:
5222:
5219:
5218:
5216:
5214:
5210:
5204:
5201:
5199:
5196:
5194:
5191:
5190:
5188:
5184:
5178:
5175:
5174:
5172:
5170:
5166:
5154:
5151:
5149:
5146:
5144:
5141:
5140:
5139:
5136:
5134:
5131:
5130:
5128:
5126:
5122:
5116:
5113:
5111:
5108:
5106:
5103:
5101:
5098:
5096:
5093:
5091:
5088:
5086:
5083:
5082:
5080:
5078:
5074:
5068:
5065:
5063:
5060:
5056:
5053:
5051:
5048:
5046:
5043:
5041:
5038:
5036:
5033:
5031:
5028:
5026:
5023:
5021:
5018:
5016:
5013:
5011:
5008:
5007:
5006:
5003:
5002:
5000:
4998:
4994:
4991:
4989:
4985:
4981:
4977:
4972:
4968:
4962:
4959:
4957:
4954:
4953:
4950:
4946:
4939:
4934:
4932:
4927:
4925:
4920:
4919:
4916:
4909:
4906:
4905:
4895:
4889:
4880:
4875:
4871:
4867:
4862:
4859:
4857:0-85264-199-0
4853:
4849:
4844:
4840:
4836:
4832:
4828:
4823:
4820:
4818:0-940600-14-5
4814:
4810:
4805:
4802:
4800:0-521-81099-X
4796:
4792:
4787:
4783:
4779:
4775:
4771:
4767:
4763:
4762:
4761:Psychometrika
4756:
4755:
4742:
4740:9780852641996
4736:
4732:
4725:
4717:
4713:
4709:
4705:
4701:
4697:
4696:
4691:
4685:
4681:
4673:
4671:
4667:
4663:
4658:
4656:
4650:
4627:
4624:
4621:
4618:
4615:
4608:
4607:
4606:
4604:
4600:
4594:
4592:
4581:
4578:
4574:
4570:
4554:
4544:
4534:
4520:
4513:
4495:
4491:
4487:
4482:
4478:
4474:
4469:
4465:
4435:
4432:
4427:
4423:
4416:
4409:
4404:
4400:
4394:
4389:
4386:
4383:
4379:
4375:
4369:
4366:
4363:
4354:
4337:
4334:
4327:
4322:
4318:
4312:
4307:
4304:
4301:
4297:
4290:
4287:
4284:
4274:
4273:
4272:
4246:
4235:
4221:
4213:
4209:
4194:
4191:
4189:
4176:
4172:
4166:
4161:
4158:
4155:
4151:
4145:
4142:
4129:
4125:
4119:
4114:
4111:
4108:
4104:
4098:
4095:
4087:
4084:
4079:
4074:
4070:
4064:
4059:
4056:
4053:
4049:
4043:
4040:
4035:
4032:
4030:
4017:
4013:
4007:
4003:
3999:
3996:
3991:
3986:
3982:
3978:
3973:
3968:
3964:
3955:
3950:
3947:
3944:
3941:
3938:
3934:
3930:
3927:
3920:
3916:
3912:
3907:
3905:
3898:
3888:
3884:
3880:
3875:
3871:
3862:
3857:
3854:
3851:
3848:
3845:
3841:
3833:
3829:
3825:
3812:
3811:
3810:
3787:
3782:
3778:
3772:
3767:
3764:
3761:
3757:
3751:
3748:
3743:
3735:
3724:
3710:
3702:
3698:
3683:
3680:
3678:
3668:
3657:
3643:
3640:
3635:
3630:
3626:
3620:
3615:
3612:
3609:
3605:
3599:
3596:
3591:
3586:
3581:
3577:
3571:
3566:
3563:
3560:
3556:
3550:
3547:
3542:
3537:
3532:
3528:
3522:
3517:
3514:
3511:
3507:
3501:
3498:
3493:
3491:
3481:
3470:
3456:
3453:
3445:
3440:
3436:
3432:
3427:
3422:
3418:
3414:
3409:
3404:
3400:
3391:
3386:
3383:
3380:
3376:
3370:
3367:
3362:
3360:
3351:
3342:
3338:
3332:
3327:
3324:
3321:
3317:
3311:
3308:
3295:
3291:
3285:
3280:
3277:
3274:
3270:
3264:
3261:
3253:
3248:
3244:
3238:
3234:
3228:
3223:
3220:
3217:
3213:
3209:
3206:
3199:
3195:
3191:
3185:
3181:
3178:
3176:
3166:
3162:
3158:
3153:
3149:
3137:
3133:
3129:
3124:
3120:
3111:
3106:
3103:
3100:
3097:
3094:
3090:
3082:
3078:
3074:
3061:
3060:
3059:
3020:
3016:
3013:
3008:
3004:
2996:
2991:
2984:
2981:
2978:
2969:
2966:
2963:
2953:
2948:
2941:
2938:
2935:
2932:
2923:
2920:
2917:
2907:
2901:
2864:
2857:
2854:
2851:
2848:
2839:
2836:
2833:
2823:
2815:
2811:
2779:
2775:
2772:
2769:
2762:
2756:
2728:
2720:
2704:
2684:
2681:
2678:
2675:
2672:
2669:
2666:
2646:
2643:
2640:
2617:
2614:
2611:
2608:
2605:
2602:
2599:
2576:
2556:
2534:
2530:
2526:
2521:
2517:
2513:
2508:
2504:
2475:
2465:
2461:
2457:
2452:
2448:
2441:
2431:
2427:
2423:
2418:
2414:
2402:
2398:
2394:
2389:
2385:
2378:
2372:
2362:
2361:
2360:
2346:
2326:
2304:
2300:
2277:
2273:
2250:
2245:
2242:
2238:
2234:
2212:
2207:
2204:
2200:
2196:
2171:
2167:
2163:
2158:
2154:
2150:
2145:
2142:
2138:
2130:
2114:
2110:
2106:
2101:
2097:
2093:
2088:
2085:
2081:
2073:
2072:
2071:
2049:
2046:
2043:
2040:
2034:
2031:
2028:
2025:
2022:
2002:
1982:
1962:
1940:
1936:
1913:
1909:
1880:
1872:
1863:
1860:
1857:
1851:
1832:
1814:
1808:
1798:
1797:
1796:
1780:
1775:
1772:
1768:
1764:
1742:
1739:
1735:
1714:
1710:
1703:
1700:
1697:
1691:
1669:
1664:
1661:
1657:
1653:
1645:
1627:
1624:
1620:
1614:
1611:
1607:
1603:
1580:
1572:
1568:
1564:
1559:
1555:
1548:
1545:
1542:
1537:
1534:
1530:
1525:
1517:
1513:
1509:
1504:
1500:
1493:
1490:
1487:
1482:
1479:
1475:
1467:
1466:
1465:
1451:
1444:-quality and
1431:
1411:
1389:
1385:
1362:
1358:
1342:
1337:
1323:
1303:
1295:
1265:
1262:
1259:
1251:
1236:
1225:
1197:
1194:
1191:
1150:
1132:
1112:
1109:
1106:
1097:
1087:
1086:
1085:
1071:
1068:
1065:
1054:
1033:
1030:
1027:
1016:
990:
987:
983:
976:
973:
948:
945:
941:
934:
931:
903:
898:
895:
891:
885:
880:
877:
874:
871:
868:
864:
858:
853:
850:
846:
840:
835:
832:
829:
826:
823:
819:
811:
808:
804:
798:
795:
791:
785:
780:
777:
774:
771:
768:
764:
757:
747:
746:
745:
711:
708:
705:
685:
682:
677:
674:
670:
666:
661:
658:
654:
631:
628:
624:
620:
617:
612:
609:
605:
582:
579:
575:
571:
568:
563:
560:
556:
533:
530:
526:
505:
483:
480:
476:
455:
435:
415:
393:
390:
387:
377:
373:
347:
344:
341:
331:
327:
303:
283:
263:
254:
240:
220:
206:
204:
200:
196:
192:
188:
184:
176:
173:
170:
169:
168:
166:
159:
158:
153:
151:
150:
145:
143:
142:
137:
135:
134:
129:
128:
127:
125:
115:
113:
109:
105:
101:
97:
96:medium income
93:
89:
84:
80:
71:
69:
65:
61:
60:nonparametric
57:
53:
49:
46:of different
45:
41:
37:
33:
19:
7226:
7214:
7195:
7188:
7100:Econometrics
7050: /
7033:Chemometrics
7010:Epidemiology
7003: /
6976:Applications
6818:ARIMA model
6765:Q-statistic
6714:Stationarity
6610:Multivariate
6553: /
6549: /
6547:Multivariate
6545: /
6485: /
6481: /
6255:Bayes factor
6154:Signed rank
6066:
6040:
6032:
6020:
5715:Completeness
5551:Cohort study
5449:Opinion poll
5384:Missing data
5371:Study design
5326:Scatter plot
5248:Scatter plot
5241:Spearman's Ï
5230:
5203:Grouped data
4888:cite journal
4869:
4865:
4847:
4833:(1): 91â95.
4830:
4826:
4808:
4790:
4765:
4759:
4730:
4724:
4699:
4693:
4684:
4669:
4665:
4661:
4659:
4654:
4651:
4647:
4602:
4598:
4595:
4587:
4576:
4572:
4568:
4546:
4456:
4270:
3808:
3058:as follows:
2495:
2188:
1900:
1595:
1349:
1180:
923:
428:-th and the
255:
212:
203:metric space
180:
162:
156:
148:
140:
132:
121:
111:
107:
103:
99:
95:
91:
85:
81:
77:
56:significance
51:
39:
35:
29:
7228:WikiProject
7143:Cartography
7105:Jurimetrics
7057:Reliability
6788:Time domain
6767:(LjungâBox)
6689:Time-series
6567:Categorical
6551:Time-series
6543:Categorical
6478:(Bernoulli)
6313:Correlation
6293:Correlation
6089:JarqueâBera
6061:Chi-squared
5823:M-estimator
5776:Asymptotics
5720:Sufficiency
5487:Interaction
5399:Replication
5379:Effect size
5336:Violin plot
5316:Radar chart
5296:Forest plot
5286:Correlogram
5236:Kendall's Ï
2319:range from
2070:defined by
1646:). The sum
187:permutation
165:coefficient
131:Spearman's
124:correlation
108:high school
100:high income
7244:Categories
7095:Demography
6813:ARMA model
6618:Regression
6195:(Friedman)
6156:(Wilcoxon)
6094:Normality
6084:Lilliefors
6031:Student's
5907:Resampling
5781:Robustness
5769:divergence
5759:Efficiency
5697:(monotone)
5692:Likelihood
5609:Population
5442:Stratified
5394:Population
5213:Dependence
5169:Count data
5100:Percentile
5077:Dispersion
5010:Arithmetic
4945:Statistics
4676:References
2741:, we have
1339:See also:
181:Following
139:Kendall's
112:university
92:low income
32:statistics
6476:Logistic
6243:posterior
6169:Rank sum
5917:Jackknife
5912:Bootstrap
5730:Bootstrap
5665:Parameter
5614:Statistic
5409:Statistic
5321:Run chart
5306:Pie chart
5301:Histogram
5291:Fan chart
5266:Bar chart
5148:L-moments
5035:Geometric
4782:122500836
4625:−
4555:ρ
4521:ρ
4488:−
4433:−
4380:∑
4370:−
4298:∑
4291:−
4282:Γ
4222:−
4152:∑
4105:∑
4085:−
4050:∑
3997:−
3935:∑
3928:⋅
3881:−
3842:∑
3758:∑
3744:−
3711:−
3641:−
3606:∑
3592:−
3557:∑
3508:∑
3454:−
3433:−
3377:∑
3318:∑
3271:∑
3254:−
3214:∑
3207:⋅
3159:−
3130:−
3091:∑
3046:Γ
3014:−
2954:−
2880:and thus
2679:…
2612:…
2527:−
2458:−
2442:∑
2424:−
2395:−
2379:∑
2370:Γ
2235:∑
2197:∑
2189:The sums
2164:−
2107:−
2044:×
2032:∈
1881:τ
1861:−
1833:−
1806:Γ
1765:∑
1701:−
1654:∑
1604:∑
1565:−
1549:
1510:−
1494:
1270:⟩
1257:⟨
1241:‖
1234:‖
1202:⟩
1189:⟨
1155:‖
1148:‖
1137:‖
1130:‖
1117:⟩
1104:⟨
1095:Γ
1069:−
1031:−
865:∑
820:∑
765:∑
755:Γ
732:Γ
621:−
572:−
391:≤
345:≤
241:ρ
221:τ
7260:Rankings
7190:Category
6883:Survival
6760:Johansen
6483:Binomial
6438:Isotonic
6025:(normal)
5670:location
5477:Blocking
5432:Sampling
5311:QâQ plot
5276:Box plot
5258:Graphics
5153:Skewness
5143:Kurtosis
5115:Variance
5045:Heronian
5040:Harmonic
2359:. Hence
1995:and the
1757:, as is
1684:is just
1596:The sum
498:, and a
155:Somers'
66:and the
44:rankings
7216:Commons
7163:Kriging
7048:Process
7005:studies
6864:Wavelet
6697:General
5864:Plug-in
5658:L space
5437:Cluster
5138:Moments
4956:Outline
4716:2281954
1222:is the
1084:, then
1008:, with
74:Context
48:ordinal
7085:Census
6675:Normal
6623:Manova
6443:Robust
6193:2-way
6185:1-way
6023:-test
5694:
5271:Biplot
5062:Median
5055:Lehmer
4997:Center
4854:
4815:
4797:
4780:
4737:
4714:
4457:where
4271:Hence
1181:where
199:metric
98:, and
6709:Trend
6238:prior
6180:anova
6069:-test
6043:-test
6035:-test
5942:Power
5887:Pivot
5680:shape
5675:scale
5125:Shape
5105:Range
5050:Heinz
5025:Cubic
4961:Index
4778:S2CID
4712:JSTOR
4605:).
189:of a
90:with
6942:Test
6142:Sign
5994:Wald
5067:Mode
5005:Mean
4894:link
4852:ISBN
4813:ISBN
4795:ISBN
4735:ISBN
3809:and
2795:and
2292:and
2227:and
1316:and
1292:the
1226:and
1046:and
966:and
597:and
362:and
296:and
34:, a
6122:BIC
6117:AIC
4874:doi
4835:doi
4770:doi
4704:doi
2339:to
1901:If
1546:sgn
1491:sgn
1350:If
698:if
191:set
30:In
7246::
4890:}}
4886:{{
4868:.
4829:.
4776:.
4766:21
4764:.
4710:.
4700:53
4698:.
4533:.
3021:12
2514::=
2151::=
2094::=
1928:,
1377:,
1336:.
110:,
106:,
94:,
70:.
6067:G
6041:F
6033:t
6021:Z
5740:V
5735:U
4937:e
4930:t
4923:v
4896:)
4876::
4870:3
4841:.
4837::
4831:2
4784:.
4772::
4743:.
4718:.
4706::
4670:r
4666:r
4662:r
4655:r
4628:u
4622:f
4619:=
4616:r
4603:u
4599:f
4577:r
4573:Y
4569:X
4496:i
4492:s
4483:i
4479:r
4475:=
4470:i
4466:d
4439:)
4436:1
4428:2
4424:n
4420:(
4417:n
4410:2
4405:i
4401:d
4395:n
4390:1
4387:=
4384:i
4376:6
4367:1
4364:=
4358:)
4355:U
4352:(
4348:r
4345:a
4342:V
4338:n
4335:2
4328:2
4323:i
4319:d
4313:n
4308:1
4305:=
4302:i
4288:1
4285:=
4252:)
4247:2
4243:)
4239:]
4236:U
4233:[
4229:E
4225:(
4219:]
4214:2
4210:U
4206:[
4202:E
4198:(
4195:2
4192:=
4182:)
4177:j
4173:r
4167:n
4162:1
4159:=
4156:j
4146:n
4143:1
4138:(
4135:)
4130:i
4126:r
4120:n
4115:1
4112:=
4109:i
4099:n
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4091:(
4088:2
4080:2
4075:i
4071:r
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4057:=
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4044:n
4041:1
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4033:=
4023:)
4018:j
4014:r
4008:i
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4000:2
3992:2
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3979:+
3974:2
3969:i
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3961:(
3956:n
3951:1
3948:=
3945:j
3942:,
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3917:n
3913:1
3908:=
3899:2
3895:)
3889:i
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3872:r
3868:(
3863:n
3858:1
3855:=
3852:j
3849:,
3846:i
3834:2
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3826:1
3788:2
3783:i
3779:d
3773:n
3768:1
3765:=
3762:i
3752:n
3749:1
3741:)
3736:2
3732:)
3728:]
3725:U
3722:[
3718:E
3714:(
3708:]
3703:2
3699:U
3695:[
3691:E
3687:(
3684:2
3681:=
3669:2
3665:)
3661:]
3658:U
3655:[
3651:E
3647:(
3644:2
3636:2
3631:i
3627:d
3621:n
3616:1
3613:=
3610:i
3600:n
3597:1
3587:2
3582:i
3578:s
3572:n
3567:1
3564:=
3561:i
3551:n
3548:1
3543:+
3538:2
3533:i
3529:r
3523:n
3518:1
3515:=
3512:i
3502:n
3499:1
3494:=
3482:2
3478:)
3474:]
3471:U
3468:[
3464:E
3460:(
3457:2
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3446:2
3441:i
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3415:+
3410:2
3405:i
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3397:(
3392:n
3387:1
3384:=
3381:i
3371:n
3368:1
3363:=
3352:)
3348:)
3343:j
3339:s
3333:n
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3325:=
3322:j
3312:n
3309:1
3304:(
3301:)
3296:i
3292:r
3286:n
3281:1
3278:=
3275:i
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3262:1
3257:(
3249:i
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3239:i
3235:r
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3221:=
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3210:n
3200:2
3196:n
3192:1
3186:(
3182:2
3179:=
3172:)
3167:i
3163:s
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3138:i
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3121:r
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3104:=
3101:j
3098:,
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3009:2
3005:n
2997:=
2992:4
2988:)
2985:1
2982:+
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2976:(
2973:)
2970:1
2967:+
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2961:(
2949:6
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2930:(
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2924:1
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2918:n
2915:(
2908:=
2905:)
2902:U
2899:(
2895:r
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2889:V
2865:6
2861:)
2858:1
2855:+
2852:n
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2846:(
2843:)
2840:1
2837:+
2834:n
2831:(
2824:=
2821:]
2816:2
2812:U
2808:[
2804:E
2780:2
2776:1
2773:+
2770:n
2763:=
2760:]
2757:U
2754:[
2750:E
2729:U
2705:U
2685:n
2682:,
2676:,
2673:2
2670:,
2667:1
2647:s
2644:,
2641:r
2621:}
2618:n
2615:,
2609:,
2606:2
2603:,
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2597:{
2577:U
2557:i
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2472:)
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2445:(
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2408:)
2403:i
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2386:r
2382:(
2373:=
2347:n
2327:1
2305:i
2301:s
2278:i
2274:r
2251:2
2246:j
2243:i
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2213:2
2208:j
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2172:i
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2139:b
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2089:j
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2058:)
2054:R
2050:;
2047:n
2041:n
2038:(
2035:M
2029:b
2026:,
2023:a
2003:y
1983:x
1963:i
1941:i
1937:s
1914:i
1910:r
1873:=
1867:)
1864:1
1858:n
1855:(
1852:n
1847:)
1844:)
1836:(
1830:)
1822:(
1819:(
1815:2
1809:=
1781:2
1776:j
1773:i
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1736:a
1715:2
1711:/
1707:)
1704:1
1698:n
1695:(
1692:n
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1665:j
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1581:.
1578:)
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1552:(
1543:=
1538:j
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1526:,
1523:)
1518:i
1514:r
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1497:(
1488:=
1483:j
1480:i
1476:a
1452:y
1432:x
1412:i
1390:i
1386:s
1363:i
1359:r
1324:B
1304:A
1275:F
1266:A
1263:,
1260:A
1252:=
1246:F
1237:A
1207:F
1198:B
1195:,
1192:A
1160:F
1151:B
1142:F
1133:A
1122:F
1113:B
1110:,
1107:A
1098:=
1072:B
1066:=
1060:T
1055:B
1034:A
1028:=
1022:T
1017:A
996:)
991:j
988:i
984:b
980:(
977:=
974:B
954:)
949:j
946:i
942:a
938:(
935:=
932:A
904:2
899:j
896:i
892:b
886:n
881:1
878:=
875:j
872:,
869:i
859:2
854:j
851:i
847:a
841:n
836:1
833:=
830:j
827:,
824:i
812:j
809:i
805:b
799:j
796:i
792:a
786:n
781:1
778:=
775:j
772:,
769:i
758:=
712:j
709:=
706:i
686:0
683:=
678:j
675:i
671:b
667:=
662:j
659:i
655:a
632:i
629:j
625:b
618:=
613:j
610:i
606:b
583:i
580:j
576:a
569:=
564:j
561:i
557:a
534:j
531:i
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506:y
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481:i
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416:i
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388:i
384:}
378:i
374:y
370:{
348:n
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338:}
332:i
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304:y
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157:D
149:Îł
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