4589:
1735:
47:
1014:
predictor variables in the model ⊠The magnitudes of the standardized regression coefficients are affected not only by the presence of correlations among the predictor variables but also by the spacings of the observations on each of these variables. Sometimes these spacings may be quite arbitrary. Hence, it is ordinarily not wise to interpret the magnitudes of standardized regression coefficients as reflecting the comparative importance of the predictor variables."
756:
816:
4575:
1448:
4613:
1010:"The standardized regression slope is the slope in the regression equation if X and Y are standardized ⊠Standardization of X and Y is done by subtracting the respective means from each set of observations and dividing by the respective standard deviations ⊠In multiple regression, where several X variables are used, the standardized regression coefficients quantify the relative contribution of each X variable."
4601:
1730:{\displaystyle {\begin{array}{l}\operatorname {Var} \left(\sum x_{i}\right)=\sum \operatorname {Var} (x_{i})=n\operatorname {Var} (x_{i})=n\sigma ^{2}\\\operatorname {Var} ({\overline {X}})=\operatorname {Var} \left({\frac {\sum x_{i}}{n}}\right)={\frac {1}{n^{2}}}\operatorname {Var} \left(\sum x_{i}\right)={\frac {n\sigma ^{2}}{n^{2}}}={\frac {\sigma ^{2}}{n}}\end{array}}}
987:"For some multivariate techniques such as multidimensional scaling and cluster analysis, the concept of distance between the units in the data is often of considerable interest and importance⊠When the variables in a multivariate data set are on different scales, it makes more sense to calculate the distances after some form of standardization."
1013:
However, Kutner et al. (p 278) give the following caveat: "⊠one must be cautious about interpreting any regression coefficients, whether standardized or not. The reason is that when the predictor variables are correlated among themselves, ⊠the regression coefficients are affected by the other
387:
Though it should always be stated, the distinction between use of the population and sample statistics often is not made. In either case, the numerator and denominator of the equations have the same units of measure so that the units cancel out through division and
265:
using this formula requires use of the population mean and the population standard deviation, not the sample mean or sample deviation. However, knowing the true mean and standard deviation of a population is often an unrealistic expectation, except in cases such as
775:
high school tests. The table shows the mean and standard deviation for total scores on the SAT and ACT. Suppose that student A scored 1800 on the SAT, and student B scored 24 on the ACT. Which student performed better relative to other test-takers?
612:
1435:
893:
273:
When the population mean and the population standard deviation are unknown, the standard score may be estimated by using the sample mean and sample standard deviation as estimates of the population values.
1133:
963:
1335:
1199:
1770:
In bone density measurements, the T-score is the standard score of the measurement compared to the population of healthy 30-year-old adults, and has the usual mean of 0 and standard deviation of 1.
672:
737:
332:
216:
514:
1255:
767:
When scores are measured on different scales, they may be converted to z-scores to aid comparison. Dietz et al. give the following example, comparing student scores on the (old)
1076:
367:
533:
461:
89:
value of what is being observed or measured. Raw scores above the mean have positive standard scores, while those below the mean have negative standard scores.
419:
for a population whose parameters are known, rather than estimated. As it is very unusual to know the entire population, the t-test is much more widely used.
979:(which is approximately correct), then the z-scores may be used to calculate the percentage of test-takers who received lower scores than students A and B.
823:
score for
Student B was 0.6, meaning Student B was 0.6 standard deviation above the mean. Thus, Student B performed in the 72.57 percentile on the SAT.
1346:
151:
Computing a z-score requires knowledge of the mean and standard deviation of the complete population to which a data point belongs; if one only has a
995:
In principal components analysis, "Variables measured on different scales or on a common scale with widely differing ranges are often standardized."
763:
score for
Student A was 1, meaning Student A was 1 standard deviation above the mean. Thus, Student A performed in the 84.13 percentile on the SAT.
3710:
4215:
4365:
3989:
2630:
830:
967:
Because student A has a higher z-score than student B, student A performed better compared to other test-takers than did student B.
3763:
1084:
155:
of observations from the population, then the analogous computation using the sample mean and sample standard deviation yields the
900:
4202:
1267:
1140:
747:
In process control applications, the Z value provides an assessment of the degree to which a process is operating off-target.
2256:
2199:
2172:
2145:
1915:
1835:
2625:
2325:
1767:
in
Japanese, where the concept is much more widely known and used in the context of high school and university admissions.
3229:
2377:
623:
2119:
2095:
2056:
1987:
1963:
1939:
683:
4012:
3904:
2282:
2014:
1890:
267:
4617:
4190:
4064:
1761:
is a standard score Z shifted and scaled to have a mean of 50 and a standard deviation of 10. It is also known as
4248:
3909:
3654:
3025:
2615:
2215:
998:
124:; the two terms may be used interchangeably, as they are in this article. Other equivalent terms in use include
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3511:
3318:
3207:
3165:
3239:
287:
180:
4542:
3501:
2404:
1852:
469:
17:
975:
Continuing the example of ACT and SAT scores, if it can be further assumed that both ACT and SAT scores are
4093:
4042:
4027:
4017:
3886:
3758:
3725:
3551:
3506:
3336:
1004:
1211:
4639:
4605:
4437:
4238:
4162:
3463:
3217:
2886:
2350:
2164:
Essentials of
Testing and Assessment: A Practical Guide for Counselors, Social Workers, and Psychologists
1049:
4322:
4294:
4289:
4037:
3796:
3702:
3682:
3590:
3301:
3119:
2602:
2474:
1789:
1023:
110:
4054:
3822:
3543:
3468:
3397:
3326:
3246:
3234:
3104:
3092:
3085:
2793:
2514:
4537:
4304:
4167:
3852:
3817:
3781:
3566:
3008:
2917:
2876:
2788:
2479:
2318:
40:
607:{\displaystyle P\left({\frac {L-\mu }{\sigma }}<Z<{\frac {U-\mu }{\sigma }}\right)=\gamma .}
4446:
4059:
3999:
3936:
3574:
3558:
3296:
3158:
3148:
2998:
2912:
1799:
1029:
343:
4484:
4414:
4207:
4144:
3899:
3786:
2783:
2680:
2587:
2466:
2365:
393:
97:
2189:
2162:
4509:
4451:
4394:
4220:
4113:
4022:
3748:
3632:
3491:
3483:
3373:
3365:
3180:
3076:
3054:
3013:
2978:
2945:
2891:
2866:
2821:
2760:
2720:
2522:
2345:
2135:
999:
Relative importance of variables in multiple regression: standardized regression coefficients
446:
4432:
4007:
3956:
3932:
3894:
3812:
3791:
3743:
3622:
3600:
3569:
3478:
3355:
3306:
3224:
3197:
3153:
3109:
2871:
2647:
2527:
2031:
1804:
1784:
100:
standard deviation. This process of converting a raw score into a standard score is called
8:
4579:
4504:
4427:
4108:
3872:
3865:
3827:
3735:
3715:
3687:
3420:
3286:
3281:
3271:
3263:
3081:
3042:
2932:
2922:
2831:
2610:
2566:
2484:
2409:
2311:
976:
428:
416:
152:
145:
51:
4593:
4404:
4258:
4154:
4103:
3979:
3876:
3860:
3837:
3614:
3348:
3331:
3291:
3202:
3097:
3059:
3030:
2990:
2950:
2896:
2813:
2499:
2494:
1763:
1079:
380:
239:
78:
55:
4588:
4499:
4469:
4461:
4281:
4272:
4197:
4128:
3984:
3969:
3944:
3832:
3773:
3639:
3627:
3253:
3170:
3114:
3037:
2881:
2803:
2582:
2456:
2278:
2252:
2195:
2168:
2141:
2115:
2091:
2052:
2010:
1983:
1959:
1935:
1911:
1886:
1831:
415:
The z-score is often used in the z-test in standardized testing â the analog of the
4524:
4479:
4243:
4230:
4123:
4098:
4032:
3964:
3842:
3450:
3343:
3276:
3189:
3136:
2955:
2826:
2620:
2504:
2419:
2386:
1860:
4441:
4185:
4047:
3974:
3649:
3523:
3496:
3473:
3442:
3069:
3064:
3018:
2748:
2399:
2246:
1430:{\displaystyle Z={\frac {{\bar {X}}-\operatorname {E} }{\sigma (X)/{\sqrt {n}}}}}
1033:
750:
170:
If the population mean and population standard deviation are known, a raw score
93:
33:
3931:
1864:
4390:
4385:
2848:
2778:
2424:
2002:
1878:
1779:
1044:
1827:
2015 European School of High-Energy
Physics: Bansko, Bulgaria 02 - 15 Sep 2015
1007:
is sometimes used as an aid to interpretation. (page 95) state the following.
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4514:
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4338:
4149:
4118:
3582:
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3141:
2843:
2670:
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2940:
2838:
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2715:
2700:
2637:
2592:
1825:
46:
32:"Standardize" redirects here. For industrial and technical standards, see
4532:
4494:
4177:
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3940:
3753:
3720:
3212:
3129:
3124:
2768:
2725:
2705:
2685:
2675:
2444:
1794:
1748:
1453:
1205:
755:
156:
1441:
Where the standardised sample mean's variance was calculated as follows:
815:
3378:
2858:
2558:
2489:
2439:
2414:
2334:
772:
258:
is negative when the raw score is below the mean, positive when above.
70:
59:
3531:
3383:
3003:
2798:
2710:
2695:
2690:
2655:
2133:
96:
from an individual raw score and then dividing the difference by the
82:
27:
How many standard deviations apart from the mean an observed datum is
1954:
Glantz, Stanton A.; Slinker, Bryan K.; Neilands, Torsten B. (2016),
431:. A prediction interval , consisting of a lower endpoint designated
3047:
2665:
2542:
2537:
2532:
2220:
NIH Osteoporosis and
Related Bone Diseases National Resource Center
2160:
4552:
4253:
982:
888:{\displaystyle z={x-\mu \over \sigma }={1800-1500 \over 300}=1}
4474:
3455:
3429:
3409:
2660:
2451:
2298:
2275:
An
Introduction to Mathematical Statistics and Its Applications
2086:
Afifi, Abdelmonem; May, Susanne K.; Clark, Virginia A. (2012),
2030:
Diez, David; Barr, Christopher; Ăetinkaya-Rundel, Mine (2012),
410:
108:(however, "normalizing" can refer to many types of ratios; see
751:
Comparison of scores measured on different scales: ACT and SAT
85:(i.e., an observed value or data point) is above or below the
2303:
2134:
John Salvia; James
Ysseldyke; Sara Witmer (29 January 2009).
2110:
Kutner, Michael; Nachtsheim, Christopher; Neter, John (204),
1128:{\displaystyle \sigma (X)={\sqrt {\operatorname {Var} (X)}}:}
970:
958:{\displaystyle z={x-\mu \over \sigma }={24-21 \over 5}=0.6}
254:
and the population mean in units of the standard deviation.
2394:
1017:
370:
229:
86:
1330:{\displaystyle {\bar {X}}={1 \over n}\sum _{i=1}^{n}X_{i}}
1830:. CERN Yellow Reports: School Proceedings. Geneva: CERN.
1194:{\displaystyle Z={X-\operatorname {E} \over \sigma (X)}}
768:
2191:
Clinical
Assessment of Child and Adolescent Intelligence
2161:
Edward S. Neukrug; R. Charles
Fawcett (1 January 2014).
2029:
2049:
An Introduction to Applied Multivariate Analysis with R
1956:
Primer of Applied Regression & Analysis of Variance
1953:
1451:
1349:
1270:
1214:
1143:
1087:
1052:
903:
833:
686:
626:
536:
472:
449:
427:
The standard score can be used in the calculation of
346:
290:
183:
4216:
Autoregressive conditional heteroskedasticity (ARCH)
2109:
2103:
1824:Mulders, Martijn; Zanderighi, Giulia, eds. (2017).
3678:
2251:(illustrated ed.). Rowman & Littlefield.
2245:Carroll, Susan Rovezzi; Carroll, David J. (2002).
2064:
2040:
1982:(First ed.), Chapman & Hall / CRC Press,
1980:Foundational and Applied Statistics for Biologists
1899:
1747:"T-score" redirects here. Not to be confused with
1729:
1429:
1329:
1249:
1204:If the random variable under consideration is the
1193:
1127:
1070:
957:
887:
731:
667:{\displaystyle P\left(-z<Z<z\right)=\gamma }
666:
606:
508:
455:
361:
326:
210:
2187:
2079:
1929:
1823:
732:{\displaystyle L=\mu -z\sigma ,\ U=\mu +z\sigma }
4631:
1947:
990:
439:, is an interval such that a future observation
3764:Multivariate adaptive regression splines (MARS)
1905:
443:will lie in the interval with high probability
250:represents the distance between that raw score
50:Comparison of the various grading methods in a
2244:
2216:"Bone Mass Measurement: What the Numbers Mean"
2137:Assessment: In Special and Inclusive Education
2070:
2046:
2009:(Fourth ed.). Wiley. p. 880, eq. 6.
1906:Spiegel, Murray R.; Stephens, Larry J (2008),
1885:(Fourth ed.). Wiley. p. 880, eq. 5.
1853:"Practical Statistics for High Energy Physics"
39:"Z-score" redirects here. For other uses, see
2319:
2085:
1923:
983:Cluster analysis and multidimensional scaling
2273:Larsen, Richard J.; Marx, Morris L. (2000).
1930:Mendenhall, William; Sincich, Terry (2007),
2071:Johnson, Richard; Wichern, Wichern (2007),
2047:Everitt, Brian; Hothorn, Torsten J (2011),
2001:
1934:(Fifth ed.), Pearson / Prentice Hall,
1932:Statistics for Engineering and the Sciences
1877:
270:, where the entire population is measured.
2364:
2326:
2312:
2272:
2090:(Fifth ed.), Chapman & Hall/CRC,
971:Percentage of observations below a z-score
2977:
2248:Statistics Made Simple for School Leaders
2073:Applied Multivariate Statistical Analysis
117:Standard scores are most commonly called
1018:Standardizing in mathematical statistics
814:
754:
617:By determining the quantile z such that
327:{\displaystyle z={x-{\bar {x}} \over S}}
211:{\displaystyle z={x-\mu \over \sigma }}
45:
2023:
1857:CERN Yellow Reports: School Proceedings
509:{\displaystyle P(L<X<U)=\gamma ,}
422:
14:
4632:
4290:KaplanâMeier estimator (product limit)
1971:
1003:Standardization of variables prior to
174:is converted into a standard score by
4363:
3930:
3677:
2976:
2746:
2363:
2307:
1850:
4600:
4300:Accelerated failure time (AFT) model
2188:Randy W. Kamphaus (16 August 2005).
1250:{\displaystyle \ X_{1},\dots ,X_{n}}
92:It is calculated by subtracting the
4612:
3895:Analysis of variance (ANOVA, anova)
2747:
2167:. Cengage Learning. pp. 133â.
1977:
1078:and dividing the difference by its
24:
3990:CochranâMantelâHaenszel statistics
2616:Pearson product-moment correlation
2238:
2140:. Cengage Learning. pp. 43â.
1374:
1159:
1071:{\displaystyle \operatorname {E} }
1053:
742:
25:
4651:
2292:
1340:then the standardized version is
435:and an upper endpoint designated
4611:
4599:
4587:
4574:
4573:
4364:
2114:(Fourth ed.), McGraw Hill,
2112:Applied Linear Regression Models
2036:(Second ed.), openintro.org
2007:Advanced Engineering Mathematics
1910:(Fourth ed.), McGraw Hill,
1883:Advanced Engineering Mathematics
4249:Least-squares spectral analysis
2277:(Third ed.). p. 282.
2208:
2181:
2154:
2127:
2088:Practical Multivariate Analysis
1958:(Third ed.), McGraw Hill,
399:
3230:Mean-unbiased minimum-variance
2333:
2222:. National Institute of Health
1995:
1871:
1844:
1817:
1580:
1567:
1538:
1525:
1510:
1497:
1409:
1403:
1395:
1389:
1380:
1365:
1277:
1185:
1179:
1171:
1165:
1117:
1111:
1097:
1091:
1065:
1059:
494:
476:
353:
312:
165:
13:
1:
4543:Geographic information system
3759:Simultaneous equations models
1810:
991:Principal components analysis
897:The z-score for student B is
827:The z-score for student A is
3726:Coefficient of determination
3337:Uniformly most powerful test
1908:Schaum's Outlines Statistics
1575:
1005:multiple regression analysis
63:
7:
4295:Proportional hazards models
4239:Spectral density estimation
4221:Vector autoregression (VAR)
3655:Maximum posterior estimator
2887:Randomized controlled trial
2194:. Springer. pp. 123â.
1865:10.23730/CYRSP-2017-004.165
1851:Gross, Eilam (2017-11-06).
1773:
1757:In educational assessment,
10:
4656:
4055:Multivariate distributions
2475:Average absolute deviation
1790:Normalization (statistics)
1746:
1742:
1024:Normalization (statistics)
1021:
408:
362:{\displaystyle {\bar {x}}}
58:, cumulative percentages,
38:
31:
4569:
4523:
4460:
4413:
4376:
4372:
4359:
4331:
4313:
4280:
4271:
4229:
4176:
4137:
4086:
4077:
4043:Structural equation model
3998:
3955:
3951:
3926:
3885:
3851:
3805:
3772:
3734:
3701:
3697:
3673:
3613:
3522:
3441:
3405:
3396:
3379:Score/Lagrange multiplier
3364:
3317:
3262:
3188:
3179:
2989:
2985:
2972:
2931:
2905:
2857:
2812:
2794:Sample size determination
2759:
2755:
2742:
2646:
2601:
2575:
2557:
2513:
2465:
2385:
2376:
2372:
2359:
2341:
2075:, Pearson / Prentice Hall
404:
4538:Environmental statistics
4060:Elliptical distributions
3853:Generalized linear model
3782:Simple linear regression
3552:HodgesâLehmann estimator
3009:Probability distribution
2918:Stochastic approximation
2480:Coefficient of variation
81:by which the value of a
41:Z-score (disambiguation)
4198:Cross-correlation (XCF)
3806:Non-standard predictors
3240:LehmannâScheffĂ© theorem
2913:Adaptive clinical trial
1800:Standard normal deviate
1030:mathematical statistics
519:For the standard score
456:{\displaystyle \gamma }
62:equivalents, z-scores,
4594:Mathematics portal
4415:Engineering statistics
4323:NelsonâAalen estimator
3900:Analysis of covariance
3787:Ordinary least squares
3711:Pearson product-moment
3115:Statistical functional
3026:Empirical distribution
2859:Controlled experiments
2588:Frequency distribution
2366:Descriptive statistics
1731:
1431:
1331:
1316:
1251:
1195:
1129:
1072:
959:
889:
824:
764:
733:
668:
608:
510:
457:
394:dimensionless quantity
363:
328:
246:The absolute value of
212:
66:
4510:Population statistics
4452:System identification
4186:Autocorrelation (ACF)
4114:Exponential smoothing
4028:Discriminant analysis
4023:Canonical correlation
3887:Partition of variance
3749:Regression validation
3593:(JonckheereâTerpstra)
3492:Likelihood-ratio test
3181:Frequentist inference
3093:Locationâscale family
3014:Sampling distribution
2979:Statistical inference
2946:Cross-sectional study
2933:Observational studies
2892:Randomized experiment
2721:Stem-and-leaf display
2523:Central limit theorem
1732:
1432:
1332:
1296:
1252:
1196:
1130:
1073:
1022:Further information:
960:
890:
818:
758:
734:
669:
609:
511:
458:
364:
329:
213:
138:standardized variable
49:
4433:Probabilistic design
4018:Principal components
3861:Exponential families
3813:Nonlinear regression
3792:General linear model
3754:Mixed effects models
3744:Errors and residuals
3721:Confounding variable
3623:Bayesian probability
3601:Van der Waerden test
3591:Ordered alternative
3356:Multiple comparisons
3235:RaoâBlackwellization
3198:Estimating equations
3154:Statistical distance
2872:Factorial experiment
2405:Arithmetic-Geometric
2033:OpenIntro Statistics
1978:Aho, Ken A. (2014),
1805:Studentized residual
1785:Mahalanobis distance
1449:
1347:
1268:
1212:
1141:
1085:
1050:
977:normally distributed
901:
831:
684:
624:
534:
470:
447:
429:prediction intervals
423:Prediction intervals
344:
288:
277:In these cases, the
268:standardized testing
181:
4505:Official statistics
4428:Methods engineering
4109:Seasonal adjustment
3877:Poisson regressions
3797:Bayesian regression
3736:Regression analysis
3716:Partial correlation
3688:Regression analysis
3287:Prediction interval
3282:Likelihood interval
3272:Confidence interval
3264:Interval estimation
3225:Unbiased estimators
3043:Model specification
2923:Up-and-down designs
2611:Partial correlation
2567:Index of dispersion
2485:Interquartile range
1859:. 4/2017: 165â186.
1208:of a random sample
1043:by subtracting its
803:Standard deviation
281:-score is given by
146:high energy physics
79:standard deviations
56:standard deviations
52:normal distribution
4640:Statistical ratios
4525:Spatial statistics
4405:Medical statistics
4305:First hitting time
4259:Whittle likelihood
3910:Degrees of freedom
3905:Multivariate ANOVA
3838:Heteroscedasticity
3650:Bayesian estimator
3615:Bayesian inference
3464:KolmogorovâSmirnov
3349:Randomization test
3319:Testing hypotheses
3292:Tolerance interval
3203:Maximum likelihood
3098:Exponential family
3031:Density estimation
2991:Statistical theory
2951:Natural experiment
2897:Scientific control
2814:Survey methodology
2500:Standard deviation
2299:z-score calculator
1727:
1725:
1427:
1327:
1247:
1191:
1125:
1080:standard deviation
1068:
955:
885:
825:
765:
729:
664:
604:
506:
453:
381:standard deviation
359:
324:
242:of the population.
240:standard deviation
232:of the population,
208:
67:
4627:
4626:
4565:
4564:
4561:
4560:
4500:National accounts
4470:Actuarial science
4462:Social statistics
4355:
4354:
4351:
4350:
4347:
4346:
4282:Survival function
4267:
4266:
4129:Granger causality
3970:Contingency table
3945:Survival analysis
3922:
3921:
3918:
3917:
3774:Linear regression
3669:
3668:
3665:
3664:
3640:Credible interval
3609:
3608:
3392:
3391:
3208:Method of moments
3077:Parametric family
3038:Statistical model
2968:
2967:
2964:
2963:
2882:Random assignment
2804:Statistical power
2738:
2737:
2734:
2733:
2583:Contingency table
2553:
2552:
2420:Generalized/power
2258:978-0-8108-4322-6
2201:978-0-387-26299-4
2174:978-1-305-16183-2
2147:978-0-547-13437-6
1917:978-0-07-148584-5
1837:978-92-9083-472-4
1721:
1701:
1640:
1616:
1578:
1425:
1422:
1392:
1368:
1294:
1280:
1217:
1189:
1120:
947:
926:
877:
856:
813:
812:
710:
588:
561:
356:
322:
315:
206:
77:is the number of
16:(Redirected from
4647:
4615:
4614:
4603:
4602:
4592:
4591:
4577:
4576:
4480:Crime statistics
4374:
4373:
4361:
4360:
4278:
4277:
4244:Fourier analysis
4231:Frequency domain
4211:
4158:
4124:Structural break
4084:
4083:
4033:Cluster analysis
3980:Log-linear model
3953:
3952:
3928:
3927:
3869:
3843:Homoscedasticity
3699:
3698:
3675:
3674:
3594:
3586:
3578:
3577:(KruskalâWallis)
3562:
3547:
3502:Cross validation
3487:
3469:AndersonâDarling
3416:
3403:
3402:
3374:Likelihood-ratio
3366:Parametric tests
3344:Permutation test
3327:1- & 2-tails
3218:Minimum distance
3190:Point estimation
3186:
3185:
3137:Optimal decision
3088:
2987:
2986:
2974:
2973:
2956:Quasi-experiment
2906:Adaptive designs
2757:
2756:
2744:
2743:
2621:Rank correlation
2383:
2382:
2374:
2373:
2361:
2360:
2328:
2321:
2314:
2305:
2304:
2288:
2269:
2267:
2265:
2232:
2231:
2229:
2227:
2212:
2206:
2205:
2185:
2179:
2178:
2158:
2152:
2151:
2131:
2125:
2124:
2107:
2101:
2100:
2083:
2077:
2076:
2068:
2062:
2061:
2044:
2038:
2037:
2027:
2021:
2020:
1999:
1993:
1992:
1975:
1969:
1968:
1951:
1945:
1944:
1927:
1921:
1920:
1903:
1897:
1896:
1875:
1869:
1868:
1848:
1842:
1841:
1821:
1736:
1734:
1733:
1728:
1726:
1722:
1717:
1716:
1707:
1702:
1700:
1699:
1690:
1689:
1688:
1675:
1670:
1666:
1665:
1664:
1641:
1639:
1638:
1626:
1621:
1617:
1612:
1611:
1610:
1597:
1579:
1571:
1556:
1555:
1537:
1536:
1509:
1508:
1484:
1480:
1479:
1478:
1436:
1434:
1433:
1428:
1426:
1424:
1423:
1418:
1416:
1398:
1394:
1393:
1385:
1370:
1369:
1361:
1357:
1336:
1334:
1333:
1328:
1326:
1325:
1315:
1310:
1295:
1287:
1282:
1281:
1273:
1256:
1254:
1253:
1248:
1246:
1245:
1227:
1226:
1215:
1200:
1198:
1197:
1192:
1190:
1188:
1174:
1151:
1134:
1132:
1131:
1126:
1121:
1104:
1077:
1075:
1074:
1069:
964:
962:
961:
956:
948:
943:
932:
927:
922:
911:
894:
892:
891:
886:
878:
873:
862:
857:
852:
841:
779:
778:
738:
736:
735:
730:
708:
673:
671:
670:
665:
657:
653:
613:
611:
610:
605:
594:
590:
589:
584:
573:
562:
557:
546:
515:
513:
512:
507:
462:
460:
459:
454:
417:Student's t-test
368:
366:
365:
360:
358:
357:
349:
333:
331:
330:
325:
323:
318:
317:
316:
308:
298:
217:
215:
214:
209:
207:
202:
191:
21:
4655:
4654:
4650:
4649:
4648:
4646:
4645:
4644:
4630:
4629:
4628:
4623:
4586:
4557:
4519:
4456:
4442:quality control
4409:
4391:Clinical trials
4368:
4343:
4327:
4315:Hazard function
4309:
4263:
4225:
4209:
4172:
4168:BreuschâGodfrey
4156:
4133:
4073:
4048:Factor analysis
3994:
3975:Graphical model
3947:
3914:
3881:
3867:
3847:
3801:
3768:
3730:
3693:
3692:
3661:
3605:
3592:
3584:
3576:
3560:
3545:
3524:Rank statistics
3518:
3497:Model selection
3485:
3443:Goodness of fit
3437:
3414:
3388:
3360:
3313:
3258:
3247:Median unbiased
3175:
3086:
3019:Order statistic
2981:
2960:
2927:
2901:
2853:
2808:
2751:
2749:Data collection
2730:
2642:
2597:
2571:
2549:
2509:
2461:
2378:Continuous data
2368:
2355:
2337:
2332:
2295:
2285:
2263:
2261:
2259:
2241:
2239:Further reading
2236:
2235:
2225:
2223:
2214:
2213:
2209:
2202:
2186:
2182:
2175:
2159:
2155:
2148:
2132:
2128:
2122:
2108:
2104:
2098:
2084:
2080:
2069:
2065:
2059:
2045:
2041:
2028:
2024:
2017:
2000:
1996:
1990:
1976:
1972:
1966:
1952:
1948:
1942:
1928:
1924:
1918:
1904:
1900:
1893:
1876:
1872:
1849:
1845:
1838:
1822:
1818:
1813:
1776:
1755:
1745:
1724:
1723:
1712:
1708:
1706:
1695:
1691:
1684:
1680:
1676:
1674:
1660:
1656:
1652:
1648:
1634:
1630:
1625:
1606:
1602:
1598:
1596:
1592:
1570:
1558:
1557:
1551:
1547:
1532:
1528:
1504:
1500:
1474:
1470:
1466:
1462:
1452:
1450:
1447:
1446:
1417:
1412:
1399:
1384:
1383:
1360:
1359:
1358:
1356:
1348:
1345:
1344:
1321:
1317:
1311:
1300:
1286:
1272:
1271:
1269:
1266:
1265:
1241:
1237:
1222:
1218:
1213:
1210:
1209:
1175:
1152:
1150:
1142:
1139:
1138:
1103:
1086:
1083:
1082:
1051:
1048:
1047:
1034:random variable
1026:
1020:
1001:
993:
985:
973:
933:
931:
912:
910:
902:
899:
898:
863:
861:
842:
840:
832:
829:
828:
753:
745:
743:Process control
685:
682:
681:
634:
630:
625:
622:
621:
574:
572:
547:
545:
544:
540:
535:
532:
531:
471:
468:
467:
448:
445:
444:
425:
413:
407:
402:
348:
347:
345:
342:
341:
307:
306:
299:
297:
289:
286:
285:
192:
190:
182:
179:
178:
168:
94:population mean
44:
37:
34:Standardization
28:
23:
22:
15:
12:
11:
5:
4653:
4643:
4642:
4625:
4624:
4622:
4621:
4609:
4597:
4583:
4570:
4567:
4566:
4563:
4562:
4559:
4558:
4556:
4555:
4550:
4545:
4540:
4535:
4529:
4527:
4521:
4520:
4518:
4517:
4512:
4507:
4502:
4497:
4492:
4487:
4482:
4477:
4472:
4466:
4464:
4458:
4457:
4455:
4454:
4449:
4444:
4435:
4430:
4425:
4419:
4417:
4411:
4410:
4408:
4407:
4402:
4397:
4388:
4386:Bioinformatics
4382:
4380:
4370:
4369:
4357:
4356:
4353:
4352:
4349:
4348:
4345:
4344:
4342:
4341:
4335:
4333:
4329:
4328:
4326:
4325:
4319:
4317:
4311:
4310:
4308:
4307:
4302:
4297:
4292:
4286:
4284:
4275:
4269:
4268:
4265:
4264:
4262:
4261:
4256:
4251:
4246:
4241:
4235:
4233:
4227:
4226:
4224:
4223:
4218:
4213:
4205:
4200:
4195:
4194:
4193:
4191:partial (PACF)
4182:
4180:
4174:
4173:
4171:
4170:
4165:
4160:
4152:
4147:
4141:
4139:
4138:Specific tests
4135:
4134:
4132:
4131:
4126:
4121:
4116:
4111:
4106:
4101:
4096:
4090:
4088:
4081:
4075:
4074:
4072:
4071:
4070:
4069:
4068:
4067:
4052:
4051:
4050:
4040:
4038:Classification
4035:
4030:
4025:
4020:
4015:
4010:
4004:
4002:
3996:
3995:
3993:
3992:
3987:
3985:McNemar's test
3982:
3977:
3972:
3967:
3961:
3959:
3949:
3948:
3924:
3923:
3920:
3919:
3916:
3915:
3913:
3912:
3907:
3902:
3897:
3891:
3889:
3883:
3882:
3880:
3879:
3863:
3857:
3855:
3849:
3848:
3846:
3845:
3840:
3835:
3830:
3825:
3823:Semiparametric
3820:
3815:
3809:
3807:
3803:
3802:
3800:
3799:
3794:
3789:
3784:
3778:
3776:
3770:
3769:
3767:
3766:
3761:
3756:
3751:
3746:
3740:
3738:
3732:
3731:
3729:
3728:
3723:
3718:
3713:
3707:
3705:
3695:
3694:
3691:
3690:
3685:
3679:
3671:
3670:
3667:
3666:
3663:
3662:
3660:
3659:
3658:
3657:
3647:
3642:
3637:
3636:
3635:
3630:
3619:
3617:
3611:
3610:
3607:
3606:
3604:
3603:
3598:
3597:
3596:
3588:
3580:
3564:
3561:(MannâWhitney)
3556:
3555:
3554:
3541:
3540:
3539:
3528:
3526:
3520:
3519:
3517:
3516:
3515:
3514:
3509:
3504:
3494:
3489:
3486:(ShapiroâWilk)
3481:
3476:
3471:
3466:
3461:
3453:
3447:
3445:
3439:
3438:
3436:
3435:
3427:
3418:
3406:
3400:
3398:Specific tests
3394:
3393:
3390:
3389:
3387:
3386:
3381:
3376:
3370:
3368:
3362:
3361:
3359:
3358:
3353:
3352:
3351:
3341:
3340:
3339:
3329:
3323:
3321:
3315:
3314:
3312:
3311:
3310:
3309:
3304:
3294:
3289:
3284:
3279:
3274:
3268:
3266:
3260:
3259:
3257:
3256:
3251:
3250:
3249:
3244:
3243:
3242:
3237:
3222:
3221:
3220:
3215:
3210:
3205:
3194:
3192:
3183:
3177:
3176:
3174:
3173:
3168:
3163:
3162:
3161:
3151:
3146:
3145:
3144:
3134:
3133:
3132:
3127:
3122:
3112:
3107:
3102:
3101:
3100:
3095:
3090:
3074:
3073:
3072:
3067:
3062:
3052:
3051:
3050:
3045:
3035:
3034:
3033:
3023:
3022:
3021:
3011:
3006:
3001:
2995:
2993:
2983:
2982:
2970:
2969:
2966:
2965:
2962:
2961:
2959:
2958:
2953:
2948:
2943:
2937:
2935:
2929:
2928:
2926:
2925:
2920:
2915:
2909:
2907:
2903:
2902:
2900:
2899:
2894:
2889:
2884:
2879:
2874:
2869:
2863:
2861:
2855:
2854:
2852:
2851:
2849:Standard error
2846:
2841:
2836:
2835:
2834:
2829:
2818:
2816:
2810:
2809:
2807:
2806:
2801:
2796:
2791:
2786:
2781:
2779:Optimal design
2776:
2771:
2765:
2763:
2753:
2752:
2740:
2739:
2736:
2735:
2732:
2731:
2729:
2728:
2723:
2718:
2713:
2708:
2703:
2698:
2693:
2688:
2683:
2678:
2673:
2668:
2663:
2658:
2652:
2650:
2644:
2643:
2641:
2640:
2635:
2634:
2633:
2628:
2618:
2613:
2607:
2605:
2599:
2598:
2596:
2595:
2590:
2585:
2579:
2577:
2576:Summary tables
2573:
2572:
2570:
2569:
2563:
2561:
2555:
2554:
2551:
2550:
2548:
2547:
2546:
2545:
2540:
2535:
2525:
2519:
2517:
2511:
2510:
2508:
2507:
2502:
2497:
2492:
2487:
2482:
2477:
2471:
2469:
2463:
2462:
2460:
2459:
2454:
2449:
2448:
2447:
2442:
2437:
2432:
2427:
2422:
2417:
2412:
2410:Contraharmonic
2407:
2402:
2391:
2389:
2380:
2370:
2369:
2357:
2356:
2354:
2353:
2348:
2342:
2339:
2338:
2331:
2330:
2323:
2316:
2308:
2302:
2301:
2294:
2293:External links
2291:
2290:
2289:
2283:
2270:
2257:
2240:
2237:
2234:
2233:
2207:
2200:
2180:
2173:
2153:
2146:
2126:
2121:978-0073014661
2120:
2102:
2097:978-1439816806
2096:
2078:
2063:
2058:978-1441996497
2057:
2039:
2022:
2015:
1994:
1989:978-1439873380
1988:
1970:
1965:978-0071824118
1964:
1946:
1941:978-0131877061
1940:
1922:
1916:
1898:
1891:
1870:
1843:
1836:
1815:
1814:
1812:
1809:
1808:
1807:
1802:
1797:
1792:
1787:
1782:
1780:Error function
1775:
1772:
1744:
1741:
1740:
1739:
1737:
1720:
1715:
1711:
1705:
1698:
1694:
1687:
1683:
1679:
1673:
1669:
1663:
1659:
1655:
1651:
1647:
1644:
1637:
1633:
1629:
1624:
1620:
1615:
1609:
1605:
1601:
1595:
1591:
1588:
1585:
1582:
1577:
1574:
1569:
1566:
1563:
1560:
1559:
1554:
1550:
1546:
1543:
1540:
1535:
1531:
1527:
1524:
1521:
1518:
1515:
1512:
1507:
1503:
1499:
1496:
1493:
1490:
1487:
1483:
1477:
1473:
1469:
1465:
1461:
1458:
1455:
1454:
1444:
1442:
1439:
1437:
1421:
1415:
1411:
1408:
1405:
1402:
1397:
1391:
1388:
1382:
1379:
1376:
1373:
1367:
1364:
1355:
1352:
1338:
1337:
1324:
1320:
1314:
1309:
1306:
1303:
1299:
1293:
1290:
1285:
1279:
1276:
1244:
1240:
1236:
1233:
1230:
1225:
1221:
1202:
1201:
1187:
1184:
1181:
1178:
1173:
1170:
1167:
1164:
1161:
1158:
1155:
1149:
1146:
1124:
1119:
1116:
1113:
1110:
1107:
1102:
1099:
1096:
1093:
1090:
1067:
1064:
1061:
1058:
1055:
1045:expected value
1019:
1016:
1000:
997:
992:
989:
984:
981:
972:
969:
954:
951:
946:
942:
939:
936:
930:
925:
921:
918:
915:
909:
906:
884:
881:
876:
872:
869:
866:
860:
855:
851:
848:
845:
839:
836:
811:
810:
807:
804:
800:
799:
796:
793:
789:
788:
785:
782:
752:
749:
744:
741:
740:
739:
728:
725:
722:
719:
716:
713:
707:
704:
701:
698:
695:
692:
689:
675:
674:
663:
660:
656:
652:
649:
646:
643:
640:
637:
633:
629:
615:
614:
603:
600:
597:
593:
587:
583:
580:
577:
571:
568:
565:
560:
556:
553:
550:
543:
539:
517:
516:
505:
502:
499:
496:
493:
490:
487:
484:
481:
478:
475:
452:
424:
421:
409:Main article:
406:
403:
401:
398:
385:
384:
383:of the sample.
374:
373:of the sample,
355:
352:
335:
334:
321:
314:
311:
305:
302:
296:
293:
244:
243:
233:
219:
218:
205:
201:
198:
195:
189:
186:
167:
164:
75:standard score
26:
9:
6:
4:
3:
2:
4652:
4641:
4638:
4637:
4635:
4620:
4619:
4610:
4608:
4607:
4598:
4596:
4595:
4590:
4584:
4582:
4581:
4572:
4571:
4568:
4554:
4551:
4549:
4548:Geostatistics
4546:
4544:
4541:
4539:
4536:
4534:
4531:
4530:
4528:
4526:
4522:
4516:
4515:Psychometrics
4513:
4511:
4508:
4506:
4503:
4501:
4498:
4496:
4493:
4491:
4488:
4486:
4483:
4481:
4478:
4476:
4473:
4471:
4468:
4467:
4465:
4463:
4459:
4453:
4450:
4448:
4445:
4443:
4439:
4436:
4434:
4431:
4429:
4426:
4424:
4421:
4420:
4418:
4416:
4412:
4406:
4403:
4401:
4398:
4396:
4392:
4389:
4387:
4384:
4383:
4381:
4379:
4378:Biostatistics
4375:
4371:
4367:
4362:
4358:
4340:
4339:Log-rank test
4337:
4336:
4334:
4330:
4324:
4321:
4320:
4318:
4316:
4312:
4306:
4303:
4301:
4298:
4296:
4293:
4291:
4288:
4287:
4285:
4283:
4279:
4276:
4274:
4270:
4260:
4257:
4255:
4252:
4250:
4247:
4245:
4242:
4240:
4237:
4236:
4234:
4232:
4228:
4222:
4219:
4217:
4214:
4212:
4210:(BoxâJenkins)
4206:
4204:
4201:
4199:
4196:
4192:
4189:
4188:
4187:
4184:
4183:
4181:
4179:
4175:
4169:
4166:
4164:
4163:DurbinâWatson
4161:
4159:
4153:
4151:
4148:
4146:
4145:DickeyâFuller
4143:
4142:
4140:
4136:
4130:
4127:
4125:
4122:
4120:
4119:Cointegration
4117:
4115:
4112:
4110:
4107:
4105:
4102:
4100:
4097:
4095:
4094:Decomposition
4092:
4091:
4089:
4085:
4082:
4080:
4076:
4066:
4063:
4062:
4061:
4058:
4057:
4056:
4053:
4049:
4046:
4045:
4044:
4041:
4039:
4036:
4034:
4031:
4029:
4026:
4024:
4021:
4019:
4016:
4014:
4011:
4009:
4006:
4005:
4003:
4001:
3997:
3991:
3988:
3986:
3983:
3981:
3978:
3976:
3973:
3971:
3968:
3966:
3965:Cohen's kappa
3963:
3962:
3960:
3958:
3954:
3950:
3946:
3942:
3938:
3934:
3929:
3925:
3911:
3908:
3906:
3903:
3901:
3898:
3896:
3893:
3892:
3890:
3888:
3884:
3878:
3874:
3870:
3864:
3862:
3859:
3858:
3856:
3854:
3850:
3844:
3841:
3839:
3836:
3834:
3831:
3829:
3826:
3824:
3821:
3819:
3818:Nonparametric
3816:
3814:
3811:
3810:
3808:
3804:
3798:
3795:
3793:
3790:
3788:
3785:
3783:
3780:
3779:
3777:
3775:
3771:
3765:
3762:
3760:
3757:
3755:
3752:
3750:
3747:
3745:
3742:
3741:
3739:
3737:
3733:
3727:
3724:
3722:
3719:
3717:
3714:
3712:
3709:
3708:
3706:
3704:
3700:
3696:
3689:
3686:
3684:
3681:
3680:
3676:
3672:
3656:
3653:
3652:
3651:
3648:
3646:
3643:
3641:
3638:
3634:
3631:
3629:
3626:
3625:
3624:
3621:
3620:
3618:
3616:
3612:
3602:
3599:
3595:
3589:
3587:
3581:
3579:
3573:
3572:
3571:
3568:
3567:Nonparametric
3565:
3563:
3557:
3553:
3550:
3549:
3548:
3542:
3538:
3537:Sample median
3535:
3534:
3533:
3530:
3529:
3527:
3525:
3521:
3513:
3510:
3508:
3505:
3503:
3500:
3499:
3498:
3495:
3493:
3490:
3488:
3482:
3480:
3477:
3475:
3472:
3470:
3467:
3465:
3462:
3460:
3458:
3454:
3452:
3449:
3448:
3446:
3444:
3440:
3434:
3432:
3428:
3426:
3424:
3419:
3417:
3412:
3408:
3407:
3404:
3401:
3399:
3395:
3385:
3382:
3380:
3377:
3375:
3372:
3371:
3369:
3367:
3363:
3357:
3354:
3350:
3347:
3346:
3345:
3342:
3338:
3335:
3334:
3333:
3330:
3328:
3325:
3324:
3322:
3320:
3316:
3308:
3305:
3303:
3300:
3299:
3298:
3295:
3293:
3290:
3288:
3285:
3283:
3280:
3278:
3275:
3273:
3270:
3269:
3267:
3265:
3261:
3255:
3252:
3248:
3245:
3241:
3238:
3236:
3233:
3232:
3231:
3228:
3227:
3226:
3223:
3219:
3216:
3214:
3211:
3209:
3206:
3204:
3201:
3200:
3199:
3196:
3195:
3193:
3191:
3187:
3184:
3182:
3178:
3172:
3169:
3167:
3164:
3160:
3157:
3156:
3155:
3152:
3150:
3147:
3143:
3142:loss function
3140:
3139:
3138:
3135:
3131:
3128:
3126:
3123:
3121:
3118:
3117:
3116:
3113:
3111:
3108:
3106:
3103:
3099:
3096:
3094:
3091:
3089:
3083:
3080:
3079:
3078:
3075:
3071:
3068:
3066:
3063:
3061:
3058:
3057:
3056:
3053:
3049:
3046:
3044:
3041:
3040:
3039:
3036:
3032:
3029:
3028:
3027:
3024:
3020:
3017:
3016:
3015:
3012:
3010:
3007:
3005:
3002:
3000:
2997:
2996:
2994:
2992:
2988:
2984:
2980:
2975:
2971:
2957:
2954:
2952:
2949:
2947:
2944:
2942:
2939:
2938:
2936:
2934:
2930:
2924:
2921:
2919:
2916:
2914:
2911:
2910:
2908:
2904:
2898:
2895:
2893:
2890:
2888:
2885:
2883:
2880:
2878:
2875:
2873:
2870:
2868:
2865:
2864:
2862:
2860:
2856:
2850:
2847:
2845:
2844:Questionnaire
2842:
2840:
2837:
2833:
2830:
2828:
2825:
2824:
2823:
2820:
2819:
2817:
2815:
2811:
2805:
2802:
2800:
2797:
2795:
2792:
2790:
2787:
2785:
2782:
2780:
2777:
2775:
2772:
2770:
2767:
2766:
2764:
2762:
2758:
2754:
2750:
2745:
2741:
2727:
2724:
2722:
2719:
2717:
2714:
2712:
2709:
2707:
2704:
2702:
2699:
2697:
2694:
2692:
2689:
2687:
2684:
2682:
2679:
2677:
2674:
2672:
2671:Control chart
2669:
2667:
2664:
2662:
2659:
2657:
2654:
2653:
2651:
2649:
2645:
2639:
2636:
2632:
2629:
2627:
2624:
2623:
2622:
2619:
2617:
2614:
2612:
2609:
2608:
2606:
2604:
2600:
2594:
2591:
2589:
2586:
2584:
2581:
2580:
2578:
2574:
2568:
2565:
2564:
2562:
2560:
2556:
2544:
2541:
2539:
2536:
2534:
2531:
2530:
2529:
2526:
2524:
2521:
2520:
2518:
2516:
2512:
2506:
2503:
2501:
2498:
2496:
2493:
2491:
2488:
2486:
2483:
2481:
2478:
2476:
2473:
2472:
2470:
2468:
2464:
2458:
2455:
2453:
2450:
2446:
2443:
2441:
2438:
2436:
2433:
2431:
2428:
2426:
2423:
2421:
2418:
2416:
2413:
2411:
2408:
2406:
2403:
2401:
2398:
2397:
2396:
2393:
2392:
2390:
2388:
2384:
2381:
2379:
2375:
2371:
2367:
2362:
2358:
2352:
2349:
2347:
2344:
2343:
2340:
2336:
2329:
2324:
2322:
2317:
2315:
2310:
2309:
2306:
2300:
2297:
2296:
2286:
2284:0-13-922303-7
2280:
2276:
2271:
2260:
2254:
2250:
2249:
2243:
2242:
2221:
2217:
2211:
2203:
2197:
2193:
2192:
2184:
2176:
2170:
2166:
2165:
2157:
2149:
2143:
2139:
2138:
2130:
2123:
2117:
2113:
2106:
2099:
2093:
2089:
2082:
2074:
2067:
2060:
2054:
2050:
2043:
2035:
2034:
2026:
2018:
2016:0-471-02140-7
2012:
2008:
2004:
1998:
1991:
1985:
1981:
1974:
1967:
1961:
1957:
1950:
1943:
1937:
1933:
1926:
1919:
1913:
1909:
1902:
1894:
1892:0-471-02140-7
1888:
1884:
1880:
1874:
1866:
1862:
1858:
1854:
1847:
1839:
1833:
1829:
1828:
1820:
1816:
1806:
1803:
1801:
1798:
1796:
1793:
1791:
1788:
1786:
1783:
1781:
1778:
1777:
1771:
1768:
1766:
1765:
1760:
1753:
1751:
1738:
1718:
1713:
1709:
1703:
1696:
1692:
1685:
1681:
1677:
1671:
1667:
1661:
1657:
1653:
1649:
1645:
1642:
1635:
1631:
1627:
1622:
1618:
1613:
1607:
1603:
1599:
1593:
1589:
1586:
1583:
1572:
1564:
1561:
1552:
1548:
1544:
1541:
1533:
1529:
1522:
1519:
1516:
1513:
1505:
1501:
1494:
1491:
1488:
1485:
1481:
1475:
1471:
1467:
1463:
1459:
1456:
1445:
1443:
1440:
1438:
1419:
1413:
1406:
1400:
1386:
1377:
1371:
1362:
1353:
1350:
1343:
1342:
1341:
1322:
1318:
1312:
1307:
1304:
1301:
1297:
1291:
1288:
1283:
1274:
1264:
1263:
1262:
1260:
1242:
1238:
1234:
1231:
1228:
1223:
1219:
1207:
1182:
1176:
1168:
1162:
1156:
1153:
1147:
1144:
1137:
1136:
1135:
1122:
1114:
1108:
1105:
1100:
1094:
1088:
1081:
1062:
1056:
1046:
1042:
1038:
1035:
1031:
1025:
1015:
1011:
1008:
1006:
996:
988:
980:
978:
968:
965:
952:
949:
944:
940:
937:
934:
928:
923:
919:
916:
913:
907:
904:
895:
882:
879:
874:
870:
867:
864:
858:
853:
849:
846:
843:
837:
834:
822:
817:
808:
805:
802:
801:
797:
794:
791:
790:
786:
783:
781:
780:
777:
774:
770:
762:
757:
748:
726:
723:
720:
717:
714:
711:
705:
702:
699:
696:
693:
690:
687:
680:
679:
678:
661:
658:
654:
650:
647:
644:
641:
638:
635:
631:
627:
620:
619:
618:
601:
598:
595:
591:
585:
581:
578:
575:
569:
566:
563:
558:
554:
551:
548:
541:
537:
530:
529:
528:
526:
522:
503:
500:
497:
491:
488:
485:
482:
479:
473:
466:
465:
464:
450:
442:
438:
434:
430:
420:
418:
412:
397:
395:
392:is left as a
391:
382:
378:
375:
372:
350:
340:
339:
338:
319:
309:
303:
300:
294:
291:
284:
283:
282:
280:
275:
271:
269:
264:
259:
257:
253:
249:
241:
237:
234:
231:
227:
224:
223:
222:
203:
199:
196:
193:
187:
184:
177:
176:
175:
173:
163:
161:
159:
154:
149:
147:
143:
139:
135:
131:
127:
123:
121:
115:
113:
112:
111:Normalization
107:
103:
102:standardizing
99:
95:
90:
88:
84:
80:
76:
72:
65:
61:
57:
54:, including:
53:
48:
42:
35:
30:
19:
18:Standardizing
4616:
4604:
4585:
4578:
4490:Econometrics
4440: /
4423:Chemometrics
4400:Epidemiology
4393: /
4366:Applications
4208:ARIMA model
4155:Q-statistic
4104:Stationarity
4000:Multivariate
3943: /
3939: /
3937:Multivariate
3935: /
3875: /
3871: /
3645:Bayes factor
3544:Signed rank
3456:
3430:
3422:
3410:
3105:Completeness
2941:Cohort study
2839:Opinion poll
2774:Missing data
2761:Study design
2716:Scatter plot
2638:Scatter plot
2631:Spearman's Ï
2593:Grouped data
2274:
2262:. Retrieved
2247:
2224:. Retrieved
2219:
2210:
2190:
2183:
2163:
2156:
2136:
2129:
2111:
2105:
2087:
2081:
2072:
2066:
2051:, Springer,
2048:
2042:
2032:
2025:
2006:
1997:
1979:
1973:
1955:
1949:
1931:
1925:
1907:
1901:
1882:
1873:
1856:
1846:
1826:
1819:
1769:
1762:
1758:
1756:
1749:
1339:
1258:
1203:
1041:standardized
1040:
1036:
1027:
1012:
1009:
1002:
994:
986:
974:
966:
896:
826:
820:
766:
760:
746:
677:it follows:
676:
616:
524:
520:
518:
440:
436:
432:
426:
414:
400:Applications
389:
386:
376:
336:
278:
276:
272:
262:
261:Calculating
260:
255:
251:
247:
245:
235:
225:
220:
171:
169:
157:
150:
141:
137:
134:normal score
133:
129:
125:
119:
118:
116:
114:for more).
109:
105:
101:
91:
74:
68:
29:
4618:WikiProject
4533:Cartography
4495:Jurimetrics
4447:Reliability
4178:Time domain
4157:(LjungâBox)
4079:Time-series
3957:Categorical
3941:Time-series
3933:Categorical
3868:(Bernoulli)
3703:Correlation
3683:Correlation
3479:JarqueâBera
3451:Chi-squared
3213:M-estimator
3166:Asymptotics
3110:Sufficiency
2877:Interaction
2789:Replication
2769:Effect size
2726:Violin plot
2706:Radar chart
2686:Forest plot
2676:Correlogram
2626:Kendall's Ï
2003:E. Kreyszig
1879:E. Kreyszig
1795:Omega ratio
1206:sample mean
166:Calculation
130:z-statistic
106:normalizing
4485:Demography
4203:ARMA model
4008:Regression
3585:(Friedman)
3546:(Wilcoxon)
3484:Normality
3474:Lilliefors
3421:Student's
3297:Resampling
3171:Robustness
3159:divergence
3149:Efficiency
3087:(monotone)
3082:Likelihood
2999:Population
2832:Stratified
2784:Population
2603:Dependence
2559:Count data
2490:Percentile
2467:Dispersion
2400:Arithmetic
2335:Statistics
1811:References
1752:-statistic
527:it gives:
160:-statistic
98:population
71:statistics
60:percentile
3866:Logistic
3633:posterior
3559:Rank sum
3307:Jackknife
3302:Bootstrap
3120:Bootstrap
3055:Parameter
3004:Statistic
2799:Statistic
2711:Run chart
2696:Pie chart
2691:Histogram
2681:Fan chart
2656:Bar chart
2538:L-moments
2425:Geometric
1710:σ
1682:σ
1654:∑
1646:
1600:∑
1590:
1576:¯
1565:
1549:σ
1523:
1495:
1489:∑
1468:∑
1460:
1401:σ
1390:¯
1378:
1372:−
1366:¯
1298:∑
1278:¯
1232:…
1177:σ
1163:
1157:−
1109:
1089:σ
1057:
938:−
924:σ
920:μ
917:−
868:−
854:σ
850:μ
847:−
727:σ
718:μ
703:σ
697:−
694:μ
662:γ
636:−
599:γ
586:σ
582:μ
579:−
559:σ
555:μ
552:−
501:γ
451:γ
354:¯
313:¯
304:−
204:σ
200:μ
197:−
83:raw score
4634:Category
4580:Category
4273:Survival
4150:Johansen
3873:Binomial
3828:Isotonic
3415:(normal)
3060:location
2867:Blocking
2822:Sampling
2701:QâQ plot
2666:Box plot
2648:Graphics
2543:Skewness
2533:Kurtosis
2505:Variance
2435:Heronian
2430:Harmonic
2226:5 August
2005:(1979).
1881:(1979).
1774:See also
1764:hensachi
64:T-scores
4606:Commons
4553:Kriging
4438:Process
4395:studies
4254:Wavelet
4087:General
3254:Plug-in
3048:L space
2827:Cluster
2528:Moments
2346:Outline
1759:T-score
1743:T-score
463:, i.e.
379:is the
369:is the
337:where:
238:is the
228:is the
221:where:
126:z-value
122:-scores
4475:Census
4065:Normal
4013:Manova
3833:Robust
3583:2-way
3575:1-way
3413:-test
3084:
2661:Biplot
2452:Median
2445:Lehmer
2387:Center
2281:
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2255:
2198:
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1962:
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411:Z-test
405:Z-test
153:sample
73:, the
4099:Trend
3628:prior
3570:anova
3459:-test
3433:-test
3425:-test
3332:Power
3277:Pivot
3070:shape
3065:scale
2515:Shape
2495:Range
2440:Heinz
2415:Cubic
2351:Index
795:1500
792:Mean
4332:Test
3532:Sign
3384:Wald
2457:Mode
2395:Mean
2279:ISBN
2266:2009
2253:ISBN
2228:2017
2196:ISBN
2169:ISBN
2142:ISBN
2116:ISBN
2092:ISBN
2053:ISBN
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1984:ISBN
1960:ISBN
1936:ISBN
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