Handbook of parametric and nonparametric statistical procedures:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton [u.a.]
CRC Press
2011
|
| Ausgabe: | 5. ed. |
| Schriftenreihe: | A Chapman & Hall book
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index Introduction -- Outline of inferential statistical tests and measures of correlation/association -- Guidelines and decision tables for selecting the appropriate statistical procedure -- Inferential statistical tests employed with a single sample -- Inferential statistical tests employed with two independent samples (and related measures of association/correlation) -- Inferential statistical tests employed with two or more independent samples (and related measures of association/correlation) -- Inferential statistical tests employed with two or more dependent samples (and related measures of association/correlation) -- Inferential statistical tests employed with a factorial design (and related measures of association/correlation) -- Measures of association/correlation -- Multivariate statistical analysis -- Appendix: Tables |
| Beschreibung: | XXXIX, 1886 S. Ill., graph. Darst. 26 cm |
| ISBN: | 9781439858011 1439858012 |
Internformat
MARC
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| 100 | 1 | |a Sheskin, David J. |d 1941- |e Verfasser |0 (DE-588)1013718429 |4 aut | |
| 245 | 1 | 0 | |a Handbook of parametric and nonparametric statistical procedures |c David J. Sheskin |
| 250 | |a 5. ed. | ||
| 264 | 1 | |a Boca Raton [u.a.] |b CRC Press |c 2011 | |
| 300 | |a XXXIX, 1886 S. |b Ill., graph. Darst. |c 26 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a A Chapman & Hall book | |
| 500 | |a Includes bibliographical references and index | ||
| 500 | |a Introduction -- Outline of inferential statistical tests and measures of correlation/association -- Guidelines and decision tables for selecting the appropriate statistical procedure -- Inferential statistical tests employed with a single sample -- Inferential statistical tests employed with two independent samples (and related measures of association/correlation) -- Inferential statistical tests employed with two or more independent samples (and related measures of association/correlation) -- Inferential statistical tests employed with two or more dependent samples (and related measures of association/correlation) -- Inferential statistical tests employed with a factorial design (and related measures of association/correlation) -- Measures of association/correlation -- Multivariate statistical analysis -- Appendix: Tables | ||
| 650 | 4 | |a Mathematical statistics / Handbooks, manuals, etc | |
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Datensatz im Suchindex
| _version_ | 1804148402724798464 |
|---|---|
| adam_text | Table
of
Contents
with Summary of Topics
Introduction
................................................. 1
Descriptive versus inferential statistics
......................................1
Statistic versus parameter
................................................2
Levels of measurement
..................................................2
Continuous versus discrete variables
........................................4
Measures of central tendency (mode, median, mean, weighted mean, geometric
mean, and the harmonic mean)
...........................................4
Measures of variability (range; quantiles, percentiles, quartiles, and deciles;
variance and standard deviation; the coefficient of variation)
..................10
Measures of skewness and kurtosis
........................................16
Visual methods for displaying data (tables and graphs, exploratory data
analysis (stem-and-ieaf displays and boxplots))
.............................30
The normal distribution
.................................................45
Hypothesis testing
.....................................................57
A history and critique of the classical hypothesis testing model
..................68
Estimation in inferential statistics
.........................................74
Relevant concepts, issues, and terminology in conducting research (the observational
method; the experimental method; the correlational method)
.................76
Experimental design (pre-experimental designs; quasi-experimental designs;
true experimental designs; single-subject designs)
..........................83
Sampling methodologies
................................................99
Basic principles of probability
...........................................101
Parametric versus nonparametric inferential statistical tests
....................109
Uni variate
versus bivariate versus multivariate statistical procedures
............110
Selection of the appropriate statistical procedure
............................
Ill
References
..........................................................
Ill
Endnotes...........................................................115
Outline of Inferential Statistical Tests and Measures of
Correlation/Association
..................................... 131
Guidelines and Decision Tables for Selecting the Appropriate
Statistical Procedure
........................................ 139
Inferential Statistical Tests Employed with a Single Sample
....... 147
Test
1:
The Single-Sample
z
Test
.........................................149
I. Hypothesis Evaluated with Test and Relevant Background Information
......149
II. Example
.......................................................149
HI. Null versus Alternative Hypotheses
..................................149
IV. Test Computations
...............................................150
V. Interpretation of the Test Results
....................................151
VI. Additional Analytical Procedures for the Single-Sample
z
Test and/or
xiv
Handbook of Parametric and Nonparametric Statistical Procedures
Related Tests
....................................................152
VII.
Additional Discussion of the Single-Sample
z
Test
......................152
1.
The interpretation of a negative
z
value
............................152
2.
The standard error of the population mean and graphical
representation of the results of the single-sample
z
test
................153
3.
Additional examples illustrating the interpretation of a computed
z
value
.......................................................158
4.
The
z
test for a population proportion
.............................158
VIII.
Additional Examples Illustrating the Use of the Single-Sample
z
Test
.......159
References
..........................................................160
Endnotes............................................................160
Test
2:
The Single-Sample
t
Test
.........................................163
I. Hypothesis Evaluated with Test and Relevant Background Information
......163
II. Example
...............................
í
.......................164
III. Null versus Alternative Hypotheses
..................................164
IV. Test Computations
...............................................164
V. Interpretation of the Test Results
....................................166
VI. Additional Analytical Procedures for the Single-Sample
/
Test and/or
Related Tests
....................................................168
1.
Determination of the power of the single-sample
t
test and the single-
sample
z
test, and the application of Test 2a: Cohen s
d
index
.........168
2.
Computation of a confidence interval for the mean of the population
represented by a sample
........................................179
VII.
Additional Discussion of the Single-Sample
t
Test
......................189
Degrees of freedom
...........................................189
VIII.
Additional Examples Illustrating the Use of the Single-Sample
t
Test
........190
IX. Addendum
......................................................191
Statistical quality control
.........................................191
Process control
.............................................192
Acceptance sampling
........................................202
References
..........................................................205
Endnotes............................................................206
Test
3:
The Single-Sample Chi-Square Test for a Population Variance
.........211
I. Hypothesis Evaluated with Test and Relevant Background Information
......211
II. Example
.......................................................212
III. Null versus Alternative Hypotheses
..................................212
IV. Test Computations
...............................................213
V. Interpretation of the Test Results
....................................214
VI. Additional Analytical Procedures for the Single-Sample Chi-Square
Test for a Population Variance and/or Related Tests
.....................216
1.
Large sample normal approximation of the chi-square distribution
......216
2.
Computation of a confidence interval for the variance of a population
represented by a sample
........................................217
3.
Sources for computing the power of the single-sample chi-square test
for a population variance
.......................................220
VII.
Additional Discussion of the Single-Sample Chi-Square Test for a
Population Variance
..............................................220
VIII.
Additional Examples Illustrating the Use of the Single-Sample Chi-
Table of
Contents xv
Square Test
for a
Population
Variance................................
220
References
..........................................................222
Endnotes............................................................222
Test 4:
The Single-Sample Test for Evaluating
Population Skewness...........225
I. Hypothesis Evaluated with
Test and Relevant
Background
Information......225
II. Example
.......................................................226
III. Null versus Alternative Hypotheses
..................................226
IV. Test Computations
...............................................227
V. Interpretation of the Test Results
....................................229
VI. Additional Analytical Procedures for the Single-Sample Test for
Evaluating Population Skewness and/or Related Tests
...................230
VII.
Additional Discussion of the Single-Sample Test for Evaluating
Population Skewness
.............................................230
1.
Exact tables for the single-sample test for evaluating population
skewness
....................................................230
2.
Note on a nonparametric test for evaluating skewness
................230
VIII.
Additional Examples Illustrating the Use of the Single-Sample Test for
Evaluating Population Skewness
....................................231
References
..........................................................231
Endnotes............................................................231
Test
5:
The Single-Sample Test for Evaluating Population Kurtosis
............233
I. Hypothesis Evaluated with Test and Relevant Background Information
......233
II. Example
.......................................................234
III. Null versus Alternative Hypotheses
..................................234
IV. Test Computations
...............................................235
V. Interpretation of the Test Results
....................................237
VI. Additional Analytical Procedures for the Single-Sample Test for
Evaluating Population Kurtosis and/or Related Tests
.....................238
1.
Test 5a: The D Agostino-Pearson test of normality
...............238
2.
Test 5b: The Jarque-Bera test of normality
......................239
VII.
Additional Discussion of the Single-Sample Test for Evaluating
Population Kurtosis
...............................................240
1.
Exact tables for the single-sample test for evaluating population
kurtosis
.....................................................240
2.
Additional comments on tests of normality
.........................240
VIII.
Additional Examples Illustrating the Use of the Single-Sample Test for
Evaluating Population Kurtosis
.....................................241
References
..........................................................241
Endnotes............................................................242
Test
6:
The Wilcoxon Signed-Ranks Test
..................................245
I. Hypothesis Evaluated with Test and Relevant Background Information
......245
II. Example
.......................................................245
III. Null versus Alternative Hypotheses
..................................246
IV. Test Computations
...............................................246
V. Interpretation of the Test Results
....................................248
VI. Additional Analytical Procedures for the Wilcoxon Signed-Ranks Test
xv/
Handbook of Parametric and Nonpar•ametric Statistical Procedures
and/or Related Tests
..............................................250
1.
The normal approximation of the Wilcoxon
Γ
statistic for large sample
sizes
.......................................................250
2.
The correction for continuity for the normal approximation of the
Wilcoxon signed-ranks test
.....................................252
3.
Tie correction for the normal approximation of the Wilcoxon test
statistic
.....................................................253
4.
Computation of a confidence interval for a population median
..........254
VII.
Additional Discussion of the Wilcoxon Signed-Ranks Test
................255
1.
Power-efficiency of the Wilcoxon signed-ranks test and the concept
of asymptotic relative efficiency
.................................255
2.
Note on symmetric population concerning hypotheses regarding median
and mean
...................................................256
VIII.
Additional Examples Illustrating the Use of the Wilcoxon Signed-
Ranks Test
...................................................... 257
References
..........................................................258
Endnotes............................................................258
Test
7:
The Kolmogorov-Smirnov Goodness-of-Fit Test for a Single
Sample
........................................................261
I. Hypothesis Evaluated with Test and Relevant Background Information
......261
II. Example
.......................................................262
III. Null versus Alternative Hypotheses
..................................263
IV. Test Computations
...............................................264
V. Interpretation of the Test Results
....................................268
VI. Additional Analytical Procedures for the Kolmogorov-Smirnov
Goodness-of-Fit Test for a Single Sample and/or Related Tests
............269
1.
Computing a confidence interval for the Kolmogorov-Smirnov
goodness-of-fit test for a single sample
............................269
2.
The power of the Kolmogorov—Smirnov goodness-of-fit test for
a single sample
...............................................270
3.
Test 7a: The Lilliefors test for normality
........................270
VII.
Additional Discussion of the Kolmogorov-Smirnov Goodness-of-Fit
Test for a Single Sample
...........................................272
1.
Effect of sample size on the result of a goodness-of-fit test
............272
2.
The Kolmogorov—Smirnov goodness-of-fit test for a single sam¬
ple versus the chi-square goodness-of-fit test and alternative
goodness-of-fit tests
...........................................273
VIII.
Additional Example Illustrating the Use of the Kolmogorov-Smirnov
Goodness-of-Fit Test for a Single Sample
.............................273
References
..........................................................274
Endnotes............................................................275
Test
8:
The Chi-Square Goodness-of-Fit Test
..............................277
I. Hypothesis Evaluated with Test and Relevant Background Information
......277
II. Examples
.......................................................278
III. Null versus Alternative Hypotheses
..................................278
IV. Test Computations
...............................................279
V. Interpretation of the Test Results
....................................281
VI. Additional Analytical Procedures for the Chi-Square Goodness-of-Fit
Table of
Contents xvii
Test
and/or Related
Tests..........................................281
1.
Comparisons involving individual cells when k>2
..................281
2.
The analysis of standardized residuals
.............................284
3.
The correction for continuity for the chi-square goodness-of-fit test
.....285
4.
Computation of a confidence interval for the chi-square goodness-of-
fit test/confidence interval for a population proportion
................286
5.
Brief discussion of the
z
test for a population proportion
(Test 9a) and the single-sample test for the median (Test 9b)
...........289
6.
Application of the chi-square goodness-of-fit test for assessing
goodness-of-fit for a theoretical population distribution
...............289
7.
Sources for computing of the power of the chi-square goodness-of-fit
test
........................................................293
8.
Heterogeneity chi-square analysis
................................293
VII.
Additional Discussion of the Chi-Square Goodness-of-Fit Test
............297
1.
Directionality of the chi-square goodness-of-fit test
..................297
2.
Additional goodness-of-fit tests
..................................299
VIII.
Additional Examples Illustrating the Use of the Chi-Square Goodness-
of-Fit Test
......................................................300
References
..........................................................302
Endnotes............................................................303
Test
9:
The Binomial Sign Test for a Single Sample
.........................309
I. Hypothesis Evaluated with Test and Relevant Background Information
......309
II. Examples
.......................................................310
III. Null versus Alternative Hypotheses
..................................310
IV. Test Computations
...............................................311
V. Interpretation of the Test Results
....................................313
VI. Additional Analytical Procedures for the Binomial Sign Test for a
Single Sample and/or Related Tests
..................................314
1.
Test 9a: The
z
test for a population proportion (with discussion of
correction for continuity; computation of a confidence interval;
procedure for computing sample size for test of specified power;
additional comments on computation of the power of the binomial
sign test for a single sample)
....................................314
2.
Extension of the
z
test for a population proportion to evaluate the
performance of
w
subjects on
η
trials on a binomially distributed
variable
....................................................323
3.
Test 9b: The single-sample test for the median
...................325
VII.
Additional Discussion of the Binomial Sign Test for a Single Sample
.......328
1.
Evaluating goodness-of-fit for a binomial distribution
................328
VIII.
Additional Example Illustrating the Use of the Binomial Sign Test for
a Single Sample
..................................................330
IX. Addendum
......................................................331
1.
Discussion of additional discrete probability distributions and the
exponential distribution
........................................331
a. The multinomial distribution
............................331
b. The negative binomial distribution
.......................333
c. The hypergeometric distribution
.........................336
d. The
Poisson
distribution
...............................339
Computation of a confidence interval for
a Poisson
parameter
. 342
xviii
Handbook of Parametric and Nonparametric Statistical Procedures
Test 9c: Test for comparing two
Poisson
counts
..........343
Evaluating goodness-of-fit for
a Poisson
distribution
........344
e. The exponential distribution
............................346
f. The matching distribution
...............................350
2.
Conditional probability,
Bayes
theorem, Bayesian statistics, and
hypothesis testing
.............................................352
Conditional probability
..................................352
Bayes
theorem
........................................353
Bayesian hypothesis testing
...............................369
Bayesian analysis of a continuous variable
...................394
References
..........................................................398
Endnotes............................................................401
Test
10:
The Single-Sample Runs Test (and Other Tests of Randomness)
........409
I. Hypothesis Evaluated with Test and Relevant Background Information
......409
II. Example
.......................................................410
III. Null versus Alternative Hypotheses
..................................411
IV. Test Computations
...............................................411
V. Interpretation of the Test Results
....................................411
VI. Additional Analytical Procedures for the Single-Sample Runs Test
and/or Related Tests
..............................................412
1.
The normal approximation of the single-sample runs test for large
sample sizes
.................................................412
2.
The correction for continuity for the normal approximation of the
single-sample runs test
.........................................413
3.
Extension of the runs test to data with more than two categories
........414
4.
Test 10a: The runs test for serial randomness
....................415
VII.
Additional Discussion of the Single-Sample Runs Test
...................418
1.
Additional discussion of the concept of randomness
..................418
VII.
Additional Examples Illustrating the Use of the Single-Sample
Runs Test
......................................................419
IX. Addendum
......................................................422
1.
The generation of pseudorandom numbers (The midsquare method;
the midproduct method; the linear congruential method)
..............422
2.
Alternative tests of randomness
..................................427
Test 10b: The frequency test
............................427
Test 10c: The gap test
..................................429
Test lOd: The poker test
................................433
Test lOe: The maximum test
.............................433
Test lOf: The coupon collector s test
......................434
Test
10g:
The mean square successive difference test (for
serial randomness
.....................................437
Additional tests of randomness (Autocorrelation; The serial
w test; The d2 square test of random numbers; Tests of trend
analysis/time series analysis)
.............................439
References
..........................................................440
Endnotes............................................................442
Table of
Contents xix
Inferential Statistical Tests Employed with Two Independent
Samples (and Related Measures of Association/Correlation)
...... 445
Test
11:
The
t
Test for Two Independent Samples
............................447
I. Hypothesis Evaluated with Test and Relevant Background Information
......447
II. Example
.......................................................447
HI. Null versus Alternative Hypotheses
..................................448
IV. Test Computations
...............................................448
V. Interpretation of the Test Results
....................................451
VI. Additional Analytical Procedures for the
t
Test for Two Independent
Samples and/or Related Tests
.......................................452
1.
The equation for the
/
test for two independent samples when a value
for a difference other than zero is stated in the null hypothesis
..........452
2.
Test
Ila:
Hartley s Fmax test for homogeneity of variance/F test
for two population variances: Evaluation of the homogeneity of
variance assumption of the
t
test for two independent samples
..........454
3.
Computation of the power of the
t
test for two independent samples
and the application of Test lib: Cohen s
d
index
...................459
4.
Measures of magnitude of treatment effect for the
t
test for two
independent samples: Omega squared (Test lie) and Eta squared
(Test lid)
..................................................466
5.
Computation of a confidence interval for the
t
test for two independent
samples
....................................................468
6.
Test lie: The
z
test for two independent samples
.................470
VII.
Additional Discussion of the
t
Test for Two Independent Samples
..........472
1.
Unequal sample sizes
..........................................472
2.
Robustness of the
t
test for two independent samples
................473
3.
Outliers (Procedures for identifying outliers: Box-and-whisker
plot criteria; Standard deviation score criterion; Test llf: Me¬
dian absolute deviation test for identifying outliers; Test
1
1 g:
Extreme Studentized deviate test for identifying outliers;
trimming data; Winsorization) and data transformation
...............474
4.
Missing data
.................................................488
5.
Clinical trials
................................................491
6.
Tests of equivalence: Test llh: The Westlake-Schuirmann test of
equivalence of two independent treatments (and procedure for
computing sample size in reference to the power of the test)
...........494
7.
Hotelling s T2
...............................................514
VIII.
Additional Examples Illustrating the Use of the
t
Test for Two
Independent Samples
.............................................514
References
..........................................................515
Endnotes............................................................520
Test
12:
The Mann-Whitney ¿/Test
.......................................531
I. Hypothesis Evaluated with Test and Relevant Background Information
......531
II. Example
.......................................................532
III. Null versus Alternative Hypotheses
..................................532
IV. Test Computations
...............................................533
V. Interpretation of the Test Results
....................................536
jo: Handbook of Parametric and Nonpar-ameiric Statistical Procedures
VI. Additional Analytical Procedures for the Mann-Whitney
U
Test and/or
Related Tests
....................................................536
1.
The normal approximation of the Mann-Whitney
U
statistic for large
sample sizes
.................................................536
2.
The correction for continuity for the normal approximation of the
Mann-Whitney i/test
.........................................538
3.
Tie correction for the normal approximation of the Mann-Whitney
U
statistic
.....................................................539
4.
Computation of a confidence interval for a difference between the
medians of two independent populations
..........................539
VII.
Additional Discussion of the Mann-Whitney f/Test
.....................542
1.
Power-efficiency of the Mann-Whitney {/test
......................542
2.
Equivalency of the normal approximation of the Mann-Whitney
U
test and the
t
test for two independent samples
with rank orders
..............................................542
3.
Alternative nonparametric rank-order procedures for evaluating a
design involving two independent samples
.........................542
VIII.
Additional Examples Illustrating the Use of the Mann-Whitney
£/
Test
......543
IX. Addendum
......................................................544
1.
Computer-intensive tests (Randomization and permutation tests: Test
12a: The randomization test for two independent samples; Test
12b: The bootstrap; Test 12c: The jackknife; Final comments on
computer-intensive procedures)
..................................544
2.
Survival analysis (Test 12d: Kaplan-Meier estimate)
...............558
3.
Procedures for evaluating censored data in a design involving two
independent samples (Permutation test based on the median
,
Gehan s test for censored data (Test 12e), and the log-rank
test (Test 12f))
...............................................568
References
..........................................................584
Endnotes............................................................587
Test
13:
The Kolmogorov-Smirnov Test for Two Independent Samples
.........595
1.
Hypothesis Evaluated with Test and Relevant Background Information
......595
II. Example
.......................................................596
III. Null versus Alternative Hypotheses
..................................596
IV. Test Computations
...............................................598
V. Interpretation of the Test Results
....................................600
VI. Additional Analytical Procedures for the Kolmogorov-Smirnov Test for
Two Independent Samples and/or Related Tests
........................601
1.
Graphical method for computing the Kolmogorov-Smirnov test
statistic
.....................................................601
2.
Computing sample confidence intervals for the Kolmogorov—Smirnov
test for two independent samples
.................................602
3.
Large sample chi-square approximation for a one-tailed analysis of the
*
Kolmogorov-Smirnov test for two independent samples
..............602
VII.
Additional Discussion of the Kolmogorov-Smirnov Test for Two
Independent Samples
.............................................603
1.
Additional comments on the Kolmogorov-Smirnov test for two
independent samples
..........................................603
VIII.
Additional Examples Illustrating the Use of the Kolmogorov-Smirnov
Table of
Contents xxi
Test
for Two Independent Samples
..................................603
References
..........................................................604
Endnotes............................................................605
Test
14:
The Siegel-Tukey Test for Equal Variability
........................607
I. Hypothesis Evaluated with Test and Relevant Background Information
......607
II. Example
.......................................................608
III. Null versus Alternative Hypotheses
..................................608
IV. Test Computations
...............................................609
V. Interpretation of the Test Results
....................................612
VI. Additional Analytical Procedures for the Siegel-Tukey Test for Equal
Variability and/or Related Tests
.....................................612
1.
The normal approximation of the Siegel-Tukey test statistic for large
sample sizes
.................................................612
2.
The correction for continuity for the normal approximation of the
Siegel-Tukey test for equal variability
............................613
3.
Tie correction for the normal approximation of the Siegel-Tukey test
statistic
.....................................................614
4.
Adjustment of scores for the Siegel-Tukey test for equal variability
when 0t
*
02
...............................................614
VII.
Additional Discussion of the Siegel-Tukey Test for Equal Variability
.......616
1.
Analysis of the homogeneity of variance hypothesis for the same set
of data with both a parametric and nonparametric test, and the power-
efficiency of the Siegel-Tukey Test for Equal Variability
.............616
2.
Alternative nonparametric tests of dispersion
.......................617
VIII.
Additional Examples Illustrating the Use of the Siegel-Tukey Test for
Equal Variability
.................................................618
References
..........................................................619
Endnotes............................................................620
Test
15:
The Moses Test for Equal Variability
...............................623
I. Hypothesis Evaluated with Test and Relevant Background Information
......623
II. Example
.......................................................624
III. Null versus Alternative Hypotheses
..................................624
IV. Test Computations
...............................................626
V. Interpretation of the Test Results
....................................628
VI. Additional Analytical Procedures for the Moses Test for Equal
Variability and/or Related Tests
.....................................629
1.
The normal approximation of the Moses test statistic for large
sample sizes
.................................................629
VII.
Additional Discussion of the Moses Test for Equal Variability
.............630
1.
Power-efficiency of the Moses Test for equal variability
..............630
2.
Issue of repetitive resampling
...................................631
3.
Alternative nonparametric tests of dispersion
.......................631
VIII.
Additional Examples Illustrating the Use of the Moses Test for Equal
Variability
......................................................631
References
..........................................................635
Endnotes............................................................635
xxii
Handbook of Parametric and Nonparametric Statistical Procedures
Test
16:
The Chi-Square Test for
г
x c
Tables (Test 16a: The Chi-Square
Test for Homogeneity; Test 16b: The Chi-Square Test of Indepen¬
dence (employed with a single sample))
.............................637
I. Hypothesis Evaluated with Test and Relevant Background Information
......637
II. Examples
.......................................................639
III. Null versus Alternative Hypotheses
..................................640
IV. Test Computations
...............................................643
V. Interpretation of the Test Results
....................................644
VI. Additional Analytical Procedures for the Chi-Square Test for
r x c
Tables and/or Related Tests
........................................646
1.
Yates
correction for continuity
..................................646
2.
Quick computational equation for a
2
χ
2
table
......................647
3.
Evaluation of a directional alternative hypothesis in the case of a
2
χ
2
contingency table
...........................................648
4.
Test 16c: The Fisher exact test
.........*.......................649
5.
Test 16d: The
ζ
test for two independent proportions
(and computation of sample size in reference to power)
...............655
6.
Computation of a confidence interval for a difference between two
proportions
..................................................661
7.
Test 16e: The median test for independent samples
................663
8.
Extension of the chi-square test for
r
χ
с
tables to contingency tables
involving more than two rows and/or columns, and associated
comparison procedures
........................................665
9.
The analysis of standardized residuals
.............................671
10.
Sources for computing the power of the chi-square test
for
r
χ
с
tables
...............................................673
11.
Measures of association for
r x c
contingency tables
.................673
Test 16f: The contingency coefficient
.....................675
Test 16g: The phi coefficient
.............................677
Test 16h: Cramer s phi coefficient
........................678
Test 16i: Yule s
Q
.....................................679
Test 16j: The odds ratio (and the concept of relative risk)
(and Test
lój-a:
Test of significance for an odds ratio and
computation of a confidence interval for an odds ratio)
......680
Test 16k: Cohen s kappa (and computation of a confidence
interval for kappa, Test
Ібк-а:
Test of significance for
Cohen s kappa, and Test
Ібк-Ь:
Test of significance for
two independent values of Cohen s kappa)
................687
12.
Combining the results of multiple
2x2
contingency tables:
...........691
Heterogeneity chi-square analysis for a
2
χ
2
contingency table
.......................................691
Test
161:
The Mantel-Haenszel analysis/test (Test 161-a:
Test of homogeneity of odds ratios for Mantel-Haenszel
ψ
analysis, Test 161-b: Summary odds ratio for Mantel-
Haenszel analysis, and Test 161-c: Mantel-Haenszel test
of association)
........................................694
VII.
Additional Discussion of the Chi-Square Test for
r x c
Tables
..............706
1.
Equivalency of the chi-square test for
r
χ
с
tables when
с =
2
with the
t
test for two independent samples (when
r
= 2)
and the single-factor
between-subjects analysis of variance (when
r
> 2) ..................706
2.
Test of equivalence for two independent proportions: Test 16m: The
Table of
Contents xxiii
Westlake-Schuirmann
test of equivalence of two independent
proportions (and procedure for computing sample size in reference
to the power of the test)
.......................................706
3.
Test 16n: The log-likelihood ratio
..............................716
4.
Simpson s paradox
............................................718
5.
Analysis of multidimensional contingency tables through use of
a chi-square analysis
..........................................720
6.
Test 16o: Analysis of multidimensional contingency tables
with log-linear analysis
.......................................731
VIII.
Additional Examples Illustrating the Use of the Chi-Square Test for
r x c
Tables
.....................................................745
References
..........................................................748
Endnotes............................................................ 751
Inferential Statistical Tests Employed with Two Dependent
Samples (and Related Measures of Association/Correlation)
...... 761
Test
17:
The
/
Test for Two Dependent Samples
.............................763
I. Hypothesis Evaluated with Test and Relevant Background Information
......763
II. Example
.......................................................764
III. Null versus Alternative Hypotheses
..................................764
IV. Test Computations
...............................................765
V. Interpretation of the Test Results
....................................767
VI. Additional Analytical Procedures for the
/
Test for Two Dependent
Samples and/or Related Tests
.......................................768
1.
Alternative equation for the
t
test for two dependent samples
...........768
2.
The equation for the
t
test for two dependent samples when a value for
a difference other than zero is stated in the null hypothesis
............772
3.
Test 17a: The
/
test for homogeneity of variance for two depen¬
dent samples: Evaluation of the homogeneity of variance assumption
of the
t
test for two dependent samples
............................772
4.
Computation of the power of the
ŕ
test for two dependent samples and
the application of Test 17b: Cohen s
d
index
......................775
5.
Measure of magnitude of treatment effect for the
/
test for two
dependent samples: Omega squared (Test 17c)
....................781
6.
Computation of a confidence interval for the
t
test for two dependent
samples
....................................................783
7.
Test 17d: Sandler s A test
.....................................784
8.
Test 17e: The
z
test for two dependent samples
...................785
VII.
Additional Discussion of the
/
Test for Two Dependent Samples
...........788
1.
The use of matched subjects in a dependent samples design
............788
2.
Relative power of the
t
test for two dependent samples and the
/
test
for two independent samples
....................................791
3.
Counterbalancing and order effects
...............................792
4.
Analysis of a one-group
pretest-posttest
design with the
t
test for two
dependent samples
............................................794
5.
Tests of equivalence: Test 17f: The Westlake-Schuirmann test of
equivalence of two dependent treatments (and procedure for
computing sample size in reference to the power of the test)
...........796
Handbook
of Parametric
and Nonparametric Statistical Procedures
VIII.
Additional Example Illustrating the Use of the
t
Test for Two
Dependent Samples
...............................................802
References
..........................................................803
Endnotes............................................................804
Test
18:
The Wilcoxon Matched-Pairs Signed-Ranks Test
.....................809
I. Hypothesis Evaluated with Test and Relevant Background Information
......809
II. Example
.......................................................810
III. Null versus Alternative Hypotheses
..................................810
IV. Test Computations
...............................................811
V. Interpretation of the Test Results
....................................812
VI. Additional Analytical Procedures for the Wilcoxon Matched-Pairs
Signed-Ranks Test and/or Related Tests
..............................814
1.
The normal approximation of the Wilcoxon
Γ
statistic for large sample
sizes
.......................................................814
2.
The correction for continuity for the normal approximation of the
Wilcoxon matched-pairs signed-ranks test
.........................815
3.
Tie correction for the normal approximation of the Wilcoxon test
statistic
.....................................................816
4.
Computation of a confidence interval for a median difference between
two dependent populations
.....................................817
VII.
Additional Discussion of the Wilcoxon Matched-Pairs Signed-Ranks
Test
...........................................................819
1.
Power-efficiency of the Wilcoxon matched-pairs signed-ranks test
......819
2.
Probability of superiority as a measure of effect size
.................819
3.
Alternative nonparametric procedures for evaluating a design
involving two dependent samples
................................819
VIII.
Additional Examples Illustrating the Use of the Wilcoxon Matched-
Pairs Signed-Ranks Test
...........................................820
References
..........................................................820
Endnotes............................................................820
Test
19:
The Binomial Sign Test for Two Dependent Samples
..................823
I. Hypothesis Evaluated with Test and Relevant Background Information
......823
II. Example
.......................................................824
III. Null versus Alternative Hypotheses
..................................824
IV. Test Computations
...............................................825
V. Interpretation of the Test Results
....................................827
VI. Additional Analytical Procedures for the Binomial Sign Test for Two
Dependent Samples and/or Related Tests
..............................828
1.
The normal approximation of the binomial sign test for two
dependent samples with and without a correction for continuity
........828
2.
Computation of a confidence interval for the binomial sign test for
two dependent samples
........................................831
* 3.
Sources for computing the power of the binomial sign test for two
dependent samples, and comments on the asymptotic relative effi¬
ciency of the test
.............................................832
VII.
Additional Discussion of the Binomial Sign Test for Two Dependent
Samples
........................................................833
1.
The problem of an excessive number of zero difference scores
.........833
Table of
Contents xxv
2.
Equivalency of the binomial sign test for two dependent samples and
the Friedman two-way analysis of variance by ranks when
k
= 2........833
VIII.
Additional Examples Illustrating the Use of the Binomial Sign Test for
Two Dependent Samples
..........................................833
References
..........................................................833
Endnotes............................................................834
Test
20:
The McNemar Test
..............................................835
I. Hypothesis Evaluated with Test and Relevant Background Information
......835
II. Examples
.......................................................836
III. Null versus Alternative Hypotheses
..................................838
IV. Test Computations
...............................................840
V. Interpretation of the Test Results
....................................840
VI. Additional Analytical Procedures for the McNemar Test and/or Related
Tests
..........................................................841
1.
Alternative equation for the McNemar test statistic based on the
normal distribution
............................................841
2.
The correction for continuity for the McNemar test
..................842
3.
Computation of the exact binomial probability for the McNemar test
model with a small sample size
..................................843
4.
Computation of the power of the McNemar test
.....................845
5.
Computation of a confidence interval for the McNemar test
............846
6.
Computation of an odds ratio for the McNemar test
..................847
7.
Additional analytical procedures for the McNemar test
...............848
8.
Test 20a: The
Gart
test for order effects
.........................848
VII.
Additional Discussion of the McNemar Test
...........................856
1.
Alternative format for the McNemar test summary table and modified
test equation
.................................................856
2.
The effect of disregarding matching
..............................857
3.
Alternative nonparametric procedures for evaluating a design with two
dependent samples involving categorical data
.......................858
4.
Test of equivalence for two independent proportions: Test 20b: The
Westlake-Schuirmann test of equivalence of two dependent
proportions
................................................858
VIII.
Additional Examples Illustrating the Use of the McNemar Test
............868
IX. Addendum
......................................................870
Extension of the McNemar test model beyond
2x2
contingency
tables
......................................................870
1.
Test 20c: The Bowker test of internal symmetry
...............870
2.
Test 20d: The Stuart-Maxwell test of marginal homogeneity
.... 874
References
..........................................................876
Endnotes............................................................878
Inferential Statistical Tests Employed with Two or More
Independent Samples (and Related Measures of
Association/Correlation)
..................................... 883
Test
21:
The Single-Factor Between-Subjects Analysis of Variance
.............885
I. Hypothesis Evaluated with Test and Relevant Background Information
......885
xxvi
Handbook of Parametric and Nonpar ametric Statistical Procedures
II. Example
.......................................................886
III. Null versus Alternative Hypotheses
..................................886
IV. Test Computations
...............................................887
V. Interpretation of the Test Results
....................................891
VI. Additional Analytical Procedures for the Single-Factor Between-
Subjects Analysis of Variance and/or Related Tests
.....................892
1.
Comparisons following computation of the omnibus
F
value for the
single-factor between-subjects analysis of variance (Planned versus
unplanned comparisons (including simple versus complex com¬
parisons); Linear contrasts; Orthogonal comparisons; Test 21a:
Multiple
t
tests/Fisher s LSD test; Test 21b; The Bonferronl·-
Dunn test; Test 21c: Tukey sHSDtestjTw^ld: TheNewman-
Keuls test; Test 21e: The
Scheffé test;
Test 21f: The Dunnett
test; Additional discussion of comparison procedures and final
recommendations; The computation of a confidence interval for a
comparison)
.........................*.......................892
2.
Comparing the means of three or more groups when fez
4.............923
3.
Evaluation of the homogeneity of variance assumption of the single-
factor between-subjects analysis of variance (Test
Ila:
Hartley s
Fmax test for homogeneity of variance, Test 21g: The Levene Test
fór
homogeneity of variance, Test
21
h: The Brown-Forsythe test
for homogeneity of variance)
..................................924
4.
Computation of the power of the single-factor between-subjects
analysis of variance
...........................................931
5.
Measures of magnitude of treatment effect for the single-factor
between-subjects analysis of variance: Omega squared (Test
21
i),
Eta squared (Test 21j), and Cohen s
ƒ
index (Test 21k)
.............934
6.
Computation of a confidence interval for the mean of a treatment
population
..................................................938
7.
Trend analysis
...............................................940
VII.
Additional Discussion of the Single-Factor Between-Subjects Analysis
of Variance
.....................................................952
1.
Theoretical rationale underlying the single-factor between-subjects
analysis of variance
...........................................952
2.
Definitional equations for the single-factor between-subjects analysis
of variance
..................................................954
3.
Equivalency of the single-factor between-subjects analysis of variance
and the
t
test for two independent samples when
к
= 2................956
4.
Robustness of the single-factor between-subjects analysis of
variance
....................................................957
5.
Equivalency of the single-factor between-subjects analysis of variance
and the
ŕ
test for two independent samples with the chi-square test for
r
χ
с
tables when
с
= 2.........................................957
6.
The general linear model
.......................................961
7.
Fixed-effects versus random-effects models for the single-factor
between-subjects analysis of variance
.............................962
8.
Multivariate analysis of variance
(MÁNOVA)
......................963
VIII.
Additional Examples Illustrating the Use of the Single-Factor Between-
Subjects Analysis of Variance
......................................963
IX. Addendum
.....................................................964
1.
Test
211:
The Single-Factor Between-Subjects Analysis of
Table of
Contents xxvii
Covariance.................................................964
References ..........................................................
982
Endnotes............................................................985
Test 22: The Kruskal-Wallis
One-Way Analysis of Variance by Ranks
.........1001
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1001
II. Example
......................................................1002
III. Null versus Alternative Hypotheses
.................................1003
IV. Test Computations
..............................................1003
V. Interpretation of the Test Results
...................................1005
VI. Additional Analytical Procedures for the Kruskal-Wallis One-Way
Analysis of Variance by Ranks and/or Related Tests
....................1005
1
.
Tie correction for the Kruskal-Wallis one-way analysis of variance by
ranks
......................................................1005
2.
Pairwise comparisons following computation of the test statistic for
the Kruskal-Wallis one-way analysis of variance by ranks
............1006
VII.
Additional Discussion of the Kruskal-Wallis One-Way Analysis of
Variance by Ranks
..............................................1010
1.
Exact tables of the Kruskal-Wallis distribution
....................1010
2.
Equivalency of the Kruskal-Wallis one-way analysis of
variance by ranks and the Mann-Whitney
U
test when k = 2
..........1010
3.
Power-efficiency of the Kruskal—
Wallis
one-way analysis of
variance by ranks
............................................1011
4.
Alternative nonparametric rank-order procedures for evaluating a
design involving
к
independent samples
..........................1011
VIII.
Additional Examples Illustrating the Use of the Kraskal-Wallis One-
Way Analysis of Variance by Ranks
................................1012
IX. Addendum
....................................................1013
1.
Test 22a: The Jonckheere-Terpstra test for ordered
alternatives
................................................1013
References
.........................................................1020
Endnotes...........................................................1021
Test
23:
The van
der Waerden
Normal-Scores Test for
к
Independent
Samples
......................................................1027
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1027
II. Example
......................................................1028
III. Null versus Alternative Hypotheses
.................................1028
IV. Test Computations
..............................................1029
V. Interpretation of the Test Results
...................................1031
VI. Additional Analytical Procedures for the van
der
Waerden Normal-
Scores Test for
к
Independent Samples and/or Related Tests
.............1032
1.
Pairwise comparisons following computation of the test statistic for
the van
der
Waerden normal-scores test for
к
independent samples
.....1032
VII.
Additional Discussion of the van
der
Waerden Normal-Scores Test for
к
Independent Samples
...........................................1035
1.
Alternative normal-scores tests
.................................1035
VIII.
Additional Examples Illustrating the Use of the van
der
Waerden
Normal-Scores Test for
к
Independent Samples
........................1035
References
.........................................................1036
Endnotes...........................................................1037
xxviii
Handbook of Parametric and Nonparametric Statistical Procedures
Inferential Statistical Tests Employed with Two or More
Dependent Samples (and Related Measures of
Association/Correlation)
.................................... 1041
Test
24:
The Single-Factor Within-Subjects Analysis of Variance
.............1043
I. Hypothesis Evaluated with Test and Relevant Background Information
.....
Î043
II. Example
......................................................1045
III. Null versus Alternative Hypotheses
.................................1045
IV. Test Computations
..............................................1045
V. Interpretation of the Test Results
...................................1050
VI. Additional Analytical Procedures for the Single-Factor Within-Subjects
Analysis of Variance and/or Related Tests
............................1051
1.
Comparisons following computation of the omnibus
F
value for the
single-factor within-subjects analysis of variance (Test 24a: Multiple
t
tests/Fisher s LSD test; Test 24b: The
éonferroni-
Dunn test;
Test 24c: Tukey s HSD test; Test 24d: The Newman-Keuls test;
Test 24e: The
Scheffé test;
Test 24f: The Dunnett test; The compu¬
tation of a confidence interval for a comparison; Alternative method¬
ology for computing MStes for a comparison)
......................1051
2.
Comparing the means of three or more conditions when A a
4.........1059
3.
Evaluation of the sphericity assumption underlying the single-factor
within-subjects analysis of variance
.............................1061
4.
Computation of the power of the single-factor within-subjects
analysis of variance
..........................................1067
5.
Measures of magnitude of treatment effect for the single-factor
within-subjects analysis of variance: Omega squared (Test24g) and
Cohen s
ƒ
index (Test 24h)
...................................1069
6.
Computation of a confidence interval for the mean of a treatment
population
.................................................1071
7.
Test 24i: The intraclass correlation
coefficient
...................1073
VII.
Additional Discussion of the Single-Factor Within-Subjects Analysis of
Variance
......................................................1075
1.
Theoretical rationale underlying the single-factor within-subjects
analysis of variance
..........................................1075
2.
Definitional equations for the single-factor within-subjects analysis of
variance
...................................................1078
3.
Relative power of the single-factor within-subjects analysis of var¬
iance and the single-factor between-subjects analysis of variance
......1081
4.
Equivalency of the single-factor within-subjects analysis of variance
and the
/
test for two dependent samples when k-2
................1082
5.
The Latin square design
......................................1083
VIII.
Additional Examples Illustrating the Use of the Single-Factor Within-
Subjects Analysis of Variance
.....................................1085
References
.........................................................1088
Endnotes...........................................................1089
Test
25:
The Friedman Two-Way Analysis of Variance by Ranks
.............1095
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1095
II. Example
......................................................1096
Table of
Contents xxix
III.
Null versus Alternative
Hypotheses
.................................1096
IV.
Test
Computations
...............................................1097
V.
Interpretation
of the Test Results ...................................
1098
VI. Additional Analytical Procedures for the Friedman Two-Way Analysis
Variance by Ranks and/or Related Tests
.............................1099
1.
Tie correction for the Friedman two-way analysis variance
by ranks
...................................................1099
2.
Pairwise comparisons following computation of the test statistic for
the Friedman two-way analysis of variance by ranks
................1100
VII.
Additional Discussion of the Friedman Two-Way Analysis of Variance
by Ranks
......................................................1105
1.
Exact tables of the Friedman distribution
.........................1105
2.
Equivalency of the Friedman two-way analysis of variance by ranks
and the binomial sign test for two dependent samples when
к
= 2 ......1105
3.
Power-efficiency of the Friedman two-way analysis of variance
by ranks
...................................................1106
4.
Alternative nonparametric rank-order procedures for evaluating a
design involving
k
dependent samples
............................1106
5.
Relationship between the Friedman two-way analysis of variance by
ranks and Kendall s coefficient of concordance
....................1107
VIII.
Additional Examples Illustrating the Use of the Friedman Two-Way
Analysis of Variance by Ranks
.....................................1107
IX. Addendum
....................................................1108
1
.Test 25a: The Page Test for Ordered Alternatives
..................1108
References
.........................................................1113
Endnotes...........................................................1114
Test
26:
The Cochran
Q
Test
............................................1119
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1119
II. Example
......................................................1120
III. Null versus Alternative Hypotheses
.................................1120
IV. Test Computations
..............................................1120
V. Interpretation of the Test Results
...................................1122
VI. Additional Analytical Procedures for the Cochran
Q
Test and/or
Related Tests
...................................................1122
1.
Pairwise comparisons following computation of the test statistic for
the Cochran
Q
test
...........................................1122
VII.
Additional Discussion of the Cochran
Q
Test
.........................1126
1.
Issues relating to subjects who obtain the same score under all of the
experimental conditions
.......................................1126
2.
Equivalency of the Cochran
Q
test and the McNemar test when
k = 2
......................................................1127
3.
Alternative nonparametric procedures with categorical data for
evaluating a design involving
к
dependent samples
..................1129
VIII.
Additional Examples Illustrating the Use of the Cochran
Q
Test
...........1129
References
.........................................................1133
Endnotes...........................................................1134
xxx
Handbook of Parametric and Nonparametric Statistical Procedures
Inferential Statistical Test Employed with a Factorial Design
(and Related Measures of Association/Correlation)
............. 1137
Test
27:
The Between-Subjects Factorial Analysis of Variance
................1139
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1139
II. Example
......................................................1140
III. Null versus Alternative Hypotheses
.................................1140
IV. Test Computations
..............................................1142
V. Interpretation of the Test Results
...................................1148
VI. Additional Analytical Procedures for the Between-Subjects Factorial
Analysis of Variance and/or Related Tests
............................1155
1.
Comparisons following computation of the
F
values for the between-
subjects factorial analysis of variance (Test 27a: Multiple
t
tests/
Fisher s LSD test; Test 27b: The Bonferroni-Dunn test; Test 27c:
Tukey s HSD test; Test 27d: The Newman-Keuls test; Test 27e:
The
Scheffé test;
Test 27f: The Dunnett test; Comparisons between
the marginal means; Evaluation of an omnibus hypothesis involving
more than two marginal means; Comparisons between specific groups
that are a combination of both factors; The computation of a confidence
interval for a comparison; Analysis of simple effects)
...............1155
2.
Evaluation of the homogeneity of variance assumption of the between-
subjects factorial analysis of variance
............................1166
3.
Computation of the power of the between-subjects factorial analysis of
variance
...................................................1167
4.
Measures of magnitude of treatment effect for the between-subjects
factorial analysis of variance: Omega squared (Test 27g) and Cohen s
ƒ
index (Test 27h)
...........................................1169
5.
Computation of a confidence interval for the mean of a population
represented by a group
........................................1173
VII.
Additional Discussion of the Between-Subjects Factorial Analysis of
Variance
......................................................1173
1.
Theoretical rationale underlying the between-subj ects factorial analysis
of variance
.................................................1173
2.
Definitional equations for the between-subjects factorial analysis of
variance
...................................................1174
3.
Unequal sample sizes
.........................................1176
4.
The randomized-blocks design
.................................1177
5.
Additional comments on the between-subjects factorial analysis of
variance (Fixed-effects versus random-effects versus mixed-effects
models; Nested factors/hierarchical designs and designs involving more
than two factors; Screening designs)
.............................1181
VIII.
Additional Examples Illustrating the Use of the Between-Subjects
Factorial Analysis of Variance
.....................................1190
IX, Addendum
.....................................................1191
Discussion of and computational procedures for additional analysis of
variance procedures for factorial designs
.........................1191
1.
Test 27i: The factorial analysis of variance for a mixed
design
...............................................1191
Analysis of a crossover design with a factorial analysis
of variance for a mixed design
.......................1196
Table of
Contents xxxi
2. Test 27j:
Analysis of variance for a Latin square design
.....1211
3.
Test 27k: The within-subjects factorial analysis
of variance
............................................1232
4.
Analysis of higher-order factorial designs
...................1237
References
.........................................................1238
Endnotes...........................................................1239
Measures of Association/Correlation
......................... 1247
Test
28:
The Pearson Product-Moment Correlation Coefficient
...............1249
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1249
II. Example
......................................................1253
III. Null versus Alternative Hypotheses
.................................1253
IV. Test Computations
..............................................1254
V. Interpretation of the Test Results (Test 28a: Test of significance for
a Pearson product-moment correlation coefficient; The coefficient
of determination)
................................................1256
VI. Additional Analytical Procedures for the Pearson Product-Moment
Correlation Coefficient and/or Related Tests
..........................1259
1.
Derivation of a regression line
..................................1259
2.
The standard error of estimate
..................................1268
3.
Computation of a confidence interval for the value of the criterion
variable
...................................................1269
4.
Computation of a confidence interval for a Pearson product-moment
correlation coefficient
........................................1271
5.
Test 28b: Test for evaluating the hypothesis that the true
population correlation is a specific value other than zero
.........1272
6.
Computation of power for the Pearson product-moment correlation
coefficient
.................................................1273
7.
Test 28c: Test for evaluating a hypothesis on whether there is a
significant difference between two independent correlations
.......1275
8.
Test 28d: Test for evaluating a hypothesis on whether
к
indepen¬
dent correlations are homogeneous
............................1277
9.
Test 28e: Test for evaluating the null hypothesis tf0: pxz
=
pYZ
.....1278
10.
Tests for evaluating a hypothesis regarding one or more regression
coefficients (Test 28f: Test for evaluating the null hypothesis
ƒƒ„:
β
= 0;
Test 28g: Test for evaluating the null hypothesis #0:
βχ = β2) .
. . 1280
11.
Additional correlational procedures
..............................1282
VII.
Additional Discussion of the Pearson Product-Moment Correlation
Coefficient
....................................................1283
1
.
The definitional equation for the Pearson product-moment correlation
coefficient
.................................................1283
2.
Covariance
.................................................1284
3.
The homoscedasticity assumption of the Pearson product-moment
correlation coefficient
........................................1285
4.
Residuals, analysis of variance for regression analysis, and
regression diagnostics
........................................1286
5.
Autocorrelation (and Test 28h: Durbin-Watson test)
..............1297
6.
The phi coefficient as a special case of the Pearson product-moment
correlation coefficient
........................................1313
xxxii
Handbook of Parametric and Nonpar ametric Statistical Procedures
7.
Ecological correlation
........................................1314
8.
Cross-lagged panel and regression-discontinuity designs
.............1316
VIII.
Additional Examples Illustrating the Use of the Pearson Product-
Moment Correlation Coefficient
....................................1323
IX. Addendum
.....................................................1324
1.
Divariate
measures of correlation that are related to the Pearson product-
moment correlation coefficient (Test 28i: The point-biserial cor¬
relation coefficient (and Test
281-а:
Test of significance for a point-
biserial correlation coefficient); Test 28j: The biserial correlation
coefficient (and Test 28j-a: Test of significance for a biserial corre¬
lation coefficient); Test 28k: The tetrachoric correlation coefficient
(and Test 28k-a: Test of significance for a tetrachoric cor-relation
coefficient))
................................................1324
2.
Data mining
................................................1334
3.
Time series analysis
..................
í
.......................1337
References
.........................................................1353
Endnotes...........................................................1358
Test
29:
Spearman s Rank-Order Correlation Coefficient
....................1365
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1365
II. Example
......................................................1367
III. Null versus Alternative Hypotheses
.................................1367
IV. Test Computations
..............................................1368
V. Interpretation of the Test Results (Test 29a: Test of significance for
Spearman s rank-order correlation coefficient)
.....................1369
VI. Additional Analytical Procedures for Spearman s Rank-Order
Correlation Coefficient and/or Related Tests
..........................1371
1.
Tie correction for Spearman s rank-order correlation coefficient
.......1371
2.
Spearman s rank-order correlation coefficient as a special case of the
Pearson product-moment correlation coefficient
....................1373
3.
Regression analysis and Spearman s rank-order correlation
coefficient
.................................................1374
4.
Partial rank correlation
........................................1375
5.
Use of Fisher s zr transformation with Spearman s rank-order
correlation coefficient
........................................1376
VII.
Additional Discussion of Spearman s Rank-Order Correlation
Coefficient
....................................................1376
1.
The relationship between Spearman
s
rank-order correlation coefficient,
Kendall s coefficient of concordance, and the Friedman two-way
analysis of variance by ranks
...................................1376
2.
Power efficiency of Spearman s rank-order correlation coefficient
.....1379
3.
Brief discussion of Kendall s
tau: An
alternative measure of association
for two sets of ranks
..........................................1379
» 4.
Weighted rank/top-down correlation
.............................1379
VIII.
Additional Examples Illustrating the Use of the Spearman s Rank-Order
Correlation Coefficient
...........................................1380
References
.........................................................1380
Endnotes...........................................................1381
Table
of Contents
xxxiii
Test
30:
Kendall s
Tau .................................................1383
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1383
II. Example
......................................................1385
III. Null versus Alternative Hypotheses
.................................1385
IV. Test Computations
..............................................1386
V. Interpretation of the Test Results (Test 30a: Test of significance for
Kendall s
tau) .................................................1388
VI. Additional Analytical Procedures for Kendall s
Tau
and/or
Related Tests
...................................................1391
1.
Tie correction for Kendall s
tau.................................1391
2.
Regression analysis and Kendall s
tau............................1394
3.
Partial rank correlation
........................................1394
4.
Sources for computing a confidence interval for Kendall s
tau.........1394
VII.
Additional Discussion of Kendall s
Tau..............................1394
1.
Power efficiency of Kendall s
tau...............................1394
2.
Kendall s coefficient of agreement
..............................1394
VIII.
Additional Examples Illustrating the Use of Kendall s
Tau...............1394
References
.........................................................1395
Endnotes...........................................................1396
Test
31:
Kendall s Coefficient of Concordance
.............................1399
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1399
II. Example
......................................................1400
III. Null versus Alternative Hypotheses
.................................1400
IV. Test Computations
..............................................1401
V. Interpretation of the Test Results (Test 31a: Test of significance for
Kendall s coefficient of concordance)
..............................1402
VI. Additional Analytical Procedures for Kendall s Coefficient of
Concordance and/or Related Tests
..................................1403
1.
Tie correction for Kendall s coefficient of concordance
..............1403
VII.
Additional Discussion of Kendall s Coefficient of Concordance
..........1405
1.
Relationship between Kendall s coefficient of concordance and
Spearman s rank-order correlation coefficient
.....................1405
2.
Relationship between Kendall s coefficient of concordance and the
Friedman two-way analysis of variance by ranks
...................1406
3.
Weighted rank/top-down concordance
...........................1408
4.
Kendall s coefficient of concordance versus the intraclass correlation
coefficient
.................................................1408
VIII.
Additional Examples Illustrating the Use of Kendall s Coefficient of
Concordance
...................................................1410
References
.........................................................1411
Endnotes...........................................................1412
Test
32:
Goodman and Kruskal s Gamma
.................................1415
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1415
II. Example
......................................................1416
III. Null versus Alternative Hypotheses
.................................1417
IV. Test Computations
..............................................1418
V. Interpretation of the Test Results (Test 32a: Test of significance for
I
xxxiv
Handbook of Parametric and Nonparametric Statistical Procedures
Goodman and Kruskal s gamma)
.................................1421
VI. Additional Analytical Procedures for Goodman and Kruskal s Gamma
and/or Related Tests
.............................................1422
1.
The computation of a confidence interval for the value of Goodman and
Kruskal s gamma
............................................1422
2.
Test 32b: Test for evaluating the null hypothesis H0:yl=y2
.......1423
3.
Sources for computing a partial correlation coefficient for Goodman and
Kruskal s gamma
............................................1424
VII.
Additional Discussion of Goodman and Kruskal s Gamma
...............1424
1.
Relationship between Goodman and Kruskal s gamma and Yule s
Q
... 1424
2.
Somers delta as an alternative measure of association for an ordered
contingency table
............................................1424
VIII.
Additional Examples Illustrating the Use of Goodman and Kruskal s
Gamma
.......................................................1425
References
..........................................................1426
Endnotes.................................?.........................1427
Multivariate
Statistical Analysis
............................. 1429
Matrix Algebra and Multivariate Analysis
..................................1431
I. Introductory Comments on Multivariate Statistical Analysis
...............1431
II. Introduction to Matrix Algebra
.....................................1432
References
.........................................................1444
Endnotes...........................................................1444
Test
33:
Multiple Regression
............................................1445
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1445
II. Examples
......................................................1453
III. Null versus Alternative Hypotheses
.................................1453
IV/V. Test Computations and Interpretation of the Test Results
A. Test computations and interpretation of results for Example
33.1
(Computation of the multiple correlation coefficient; The coefficient of
multiple determination; Test of significance for a multiple correlation
coefficient; The multiple regression equation; The standard error of
multiple estimate; Computation of a confidence interval for
Y
;
Evalua¬
tion of the relative importance of the predictor variables; Evaluating
the significance of a regression coefficient; Computation of a confidence
interval for a regression coefficient; Analysis of variance for multiple
regression; Semipartial and partial correlation (Test 33a: Computation of
a semipartial correlation coefficient; Test of significance for a semipartial
correlation coefficient; Test 33b: Computation of a partial correlation
coefficient; Test of significance for a partial correlation coefficient)
......1454
B. Test computations and interpretation of results for Example
33.2
with SPSS
.............................................1472
VI. Additional Analytical Procedures for Multiple Regression
and/or Related Tests
.............................................1482
1.
Cross-validation of sample data
.................................1482
VII.
Additional Discussion of Multiple Regression
.........................1483
1.
Final comments on multiple regression analysis
....................1483
Table
of
Contents
xxxv
2.
Causal
modeling: Path analysis and structural
equation modeling
...........................................1484
3.
Brief note on logistic regression
................................1484
VIII.
Additional Examples Illustrating the Use of Multiple Regression
..........1485
References
.........................................................1485
Endnotes...........................................................1487
Test
34:
Hotelling s T2
..................................................1495
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1495
II. Example
......................................................1495
III. Null versus Alternative Hypotheses
.................................1496
IV. Test Computations
..............................................1497
V. Interpretation of the Test Results
...................................1498
VI. Additional Analytical Procedures for Hotelling s T2 and/or
Related Tests
...................................................1500
1.
Additional analyses following the test of the omnibus null
hypothesis
.................................................1500
2.
Test 34a: The single-sample Hotelling s
Г2
.....................1501
3.
Test 34b: The use of the single-sample Hotelling s T1 to
evaluate a dependent samples design
..........................1503
VII.
Additional Discussion of Hoteliing s T2
.............................1507
1.
Hotelling s T2 and Mahalanobis D2 statistic
......................1507
VIII.
Additional Examples Illustrating the Use of Hotelling s T2
...............1507
References
.........................................................1507
Endnotes...........................................................1508
Test
35:
Multivariate Analysis of Variance
................................1511
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1511
II, Example
......................................................1512
III. Null versus Alternative Hypotheses
.................................1513
IV. Test Computations
..............................................1514
V. Interpretation of the Test Results
...................................1515
VI
.
Additional Analytical Procedures for the Multivariate Analysis of Variance
and/or Related Tests
.............................................1522
VII.
Additional Discussion of the Multivariate Analysis of Variance
...........1522
1
.
Conceptualizing the hypothesis for the multivariate analysis of
variance within the context of a linear combination
.................1522
2.
Multicollinearity and the multivariate analysis of variance
............1522
VIII.
Additional Examples Illustrating the Use of the Multivariate
Analysis of Variance
.............................................1523
References
.........................................................1523
Endnotes...........................................................1524
Test
36:
Multivariate Analysis of Covariance
..............................1527
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1527
II. Example
......................................................1528
III. Null versus Alternative Hypotheses
.................................1529
IV. Test Computations
..............................................1529
V. Interpretation of the Test Results
...................................1530
xxxvi
Handbook of Parametric and Nonparametric Statistical Procedures
VI. Additional Analytical Procedures for the
Multi
variate
Analysis of
Covariance and/or Related Tests
....................................1533
VII.
Additional Discussion of the Multivariate Analysis of Covariance
.........1533
1.
Multiple covariates
..........................................1533
VIII.
Additional Examples Illustrating the Use of the Multivariate
Analysis of Covariance
...........................................1534
References
.........................................................1534
Endnotes...........................................................1534
Test
37:
Discriminant Function Analysis
..................................1537
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1537
II. Examples
......................................................1539
III. Null versus Alternative Hypotheses
.................................1540
IV. Test Computations
.....................
ι
........................1541
V. Interpretation of the Test Results
...................................1543
Analysis of Example
37.1 .....................................1543
Analysis of Example
37.2 .....................................1555
VI. Additional Analytical Procedures for Discriminant Function Analysis
and/or Related Tests
.............................................1564
VII.
Additional Discussion of Discriminant Function Analysis
................1564
VIII.
Additional Examples Illustrating the Use of Discriminant
Function Analysis
...............................................1564
References
.........................................................1564
Endnotes...........................................................1565
Test
38:
Canonical Correlation
..........................................1569
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1569
II. Example
......................................................1572
III. Null versus Alternative Hypotheses
.................................1572
IV. Test Computations
..............................................1572
V. Interpretation of the Test Results
...................................1573
VI. Additional Analytical Procedures for Canonical Correlation
and/or Related Tests
.............................................1586
VII.
Additional Discussion of Canonical Correlation
.......................1586
VIII.
Additional Examples Illustrating the Use of Canonical Correlation
........1587
References
.........................................................1587
Endnotes...........................................................1588
Test
39:
Logistic Regression
.............................................1593
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1593
II. Example
......................................................1596
III. Null versus Alternative Hypotheses
.................................1596
IV. Test Computations
..............................................1599
V. interpretation of the Test Results
___...............................1602
Results for a binary logistic regression with one predictor variable
.....1602
Results for a binary logistic regression with multiple predictor variables
.1610
VI. Additional Analytical Procedures for Logistic Regression
and/or Related Tests
.............................................1617
VII.
Additional Discussion of Logistic Regression
.........................1618
Table of
Contents xxxvii
VIII.
Additional Examples Illustrating the Use of Logistic Regression
..........1618
References
.........................................................1618
Endnotes...........................................................1619
Test
40:
Principal Components Analysis and Factor Analysis
.................1627
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1627
II. Example
......................................................1630
III. Null versus Alternative Hypotheses
.................................1630
IV. Test Computations
..............................................1630
V. Interpretation of the Test Results
...................................1634
VI. Additional Analytical Procedures for Principal Components Analysis
and Factor Analysis and/or Related Tests
............................1646
1.
Principal axis factor analysis of Example
40.1 .....................1646
VII.
Additional Discussion of Principal Components Analysis and
Factor Analysis
.................................................1647
1.
Criticisms of factor analytic procedures
..........................1647
2.
Cluster analysis
.............................................1647
3.
Multidimensional scaling
......................................1648
VIII.
Additional Examples Illustrating the Use of Principal Components
Analysis and Factor Analysis
......................................1649
References
.........................................................1651
Endnotes...........................................................1652
Test
41:
Path Analysis
..................................................1659
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1659
Additional discussion of basic terminology employed
in path analysis
..............................................1661
Assumptions underlying path analysis
............................1665
II. Example
......................................................1666
III. Null versus Alternative Hypotheses
.................................1666
IV. Test Computations
..............................................1668
Decomposition of correlations among pairs of variables
..............1669
Model identification
..........................................1670
Computation of degrees of freedom for a path model
................1671
Determination of the number of observations
......................1671
Determination of the number of parameters to be estimated
...........1672
Guidelines for evaluating effect values
...........................1673
Decomposition of correlations among pairs of variables in
Models A and
В
..........................................1674
V. Interpretation of the Test Results
...................................1678
Goodness-of-fit indices for a path analysis model
...................1680
VI. Additional Analytical Procedures for Path Analysis
....................1682
VII.
Additional Discussion of Path Analysis
..............................1682
VIII.
Additional Examples Illustrating the Use of Path analysis
................1683
References
.........................................................1683
Endnotes...........................................................1684
Test
42:
Structural Equation Modeling
....................................1687
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1687
xxxviii
Handbook of Parametric and Nonparametric Statistical Procedures
Assumptions underlying
SEM
..................................1689
Elements employed in a structural equation model
..................1690
Methods for summarizing a structural model
......................1691
II. Example
......................................................1699
III. Null versus Alternative Hypotheses
.................................1700
IV. Test Computations
..............................................1700
V. Interpretation of the Test Results
...................................1701
Guidelines for determining degrees of freedom
....................1701
Assessing model fit
..........................................1703
Analysis of Example
42.1 .....................................1708
VI. Additional Analytical Procedures for Structural Equation Modeling
........1713
VII.
Additional Discussion of Structural Equation Modeling
.................1713
SEM
software
..............................................1713
Additional sources
ofinformation
on
SEM
........................1713
VIII.
Additional Examples Illustrating the Use of Structural
Equation Modeling
.............................................1714
References
.........................................................1718
Endnotes...........................................................1720
Test
43:
Meta-Analysis
.................................................1725
I. Hypothesis Evaluated with Test and Relevant Background Information
.....1725
Relevant background information on meta-analysis
.................1725
Measures of effect size
.......................................1727
II. Examples
......................................................1733
III. Null versus Alternative Hypotheses
.................................1735
IV/V. Test Computations and Interpretation of Test Results
...................1735
Meta-analytic procedures employing significance level and
effect size
.............................................1735
Test 43a: Procedure for comparing
к
studies with respect to
significance level
......................................1737
Test 43b: The Stouffer procedure for obtaining a combined
significance level (p value) for
к
studies
....................1738
The file drawer problem
...................................1740
Test 43c: Homogeneity analysis for comparing
к
studies with
respect to effect size
...................................1743
Test 43d: Procedure for obtaining a combined effect size
for
к
studies
..........................................1745
Meta-analytic procedures based on weighting effect sizes with
inverse variance weights
.................................1746
Test 43e: Procedure for obtaining a weighted mean effect
size for
к
studies
......................................1753
Test 43f: Procedure for evaluating the null hypothesis that the
true value of the overall effect size in the underlying
population equals
0 ....................................1753
Test 43g: Procedure for computing a confidence interval
for the mean effect size
.................................1753
Test 43h: Homogeneity analysis for comparing
к
studies
with respect to effect size through use of inverse
variance weights
.......................................1754
VI. Additional Analytical Procedures for Meta-Analysis
....................1768
*
Table of
Contents xxxix
Graphing techniques for meta-analysis
...........................1768
Alternative meta-analytic procedures
............................1769
Practical implications of magnitude of effect size value
..............1771
Test 43i: Binomial effect size display
...........................1773
VII.
Additional Discussion of
Meta-
Analysis
.............................1775
Meta-analysis software
.......................................1775
The significance test controversy
................................1775
The minimum-effect hypothesis testing model
.....................1777
VIII.
Additional Examples Illustrating the Use of
Meta-
Analysis
..............1778
References
.........................................................1778
Endnotes...........................................................1781
Appendix: Tables
......................................... 1791
Table
Al.
Table of the Normal Distribution
..............................1795
Table A2. Table of Student s
t
Distribution
..............................1800
Table
A3.
Power Curves for Student s
/
Distribution
......................1801
Table
A4.
Table of the Chi-Square Distribution
..........................1805
Table A5. Table of Critical
Γ
Values for Wilcoxon s Signed-Ranks and
Matched-Pairs Signed-Ranks Tests
............................1806
Table A6. Table of the Binomial Distribution, Individual Probabilities
.......1807
Table A7. Table of the Binomial Distribution, Cumulative Probabilities
......1810
Table A8. Table of Critical Values for the Single-Sample Runs Test
.........1813
Table A9. Table of the Fmax Distribution
.................................1814
Table
AIO.
Table of the
F
Distribution
...................................1815
Table All. Table of Critical Values for Mann-Whitney
U
Statistic
...........1823
Table A12. Table of Sandler s
Λ
Statistic
.................................1825
Table A13. Table of the Studentized Range Statistic
........................1826
Table A14. Table of Dunnett s Modified
t
Statistic for a Control Group
Comparison
...............................................1828
Table A15. Graphs of the Power Function for the Analysis of Variance
........1830
Table A16. Table of Critical Values for Pearson
г
..........................1834
Table A17. Table of Fisher s zr Transformation
...........................1835
Table A18. Table of Critical Values for Spearman s Rho
....................1836
Table A19. Table of Critical Values for Kendall s
Tau......................1837
Table A20. Table of Critical Values for Kendall s Coefficient of
Concordance
...............................................1838
Table A21. Table of Critical Values for the Kolmogorov—Smirnov
Goodness-of-Fit Test for a Single Sample
.......................1839
Table A22. Table of Critical Values for the Lilliefors Test for Normality
......1840
Table A23. Table of Critical Values for the Kolmogorov-Smirnov Test for
Two Independent Samples
...................................1841
Table A24. Table of Critical Values for the Jonckheere-Terpstra
Test Statistic
...............................................1843
Table A25. Table of Critical Values for the Page Test Statistic
...............1845
Table A26. Table of Extreme Studentized Deviate Outlier Statistic
...........1847
Table A27. Table of Durbin-Watson Test Statistic
.........................1848
Table A28. Constants Used for Estimation and Construction of Control
Charts
....................................................1850
Index
.................................................... 1851
|
| any_adam_object | 1 |
| author | Sheskin, David J. 1941- |
| author_GND | (DE-588)1013718429 |
| author_facet | Sheskin, David J. 1941- |
| author_role | aut |
| author_sort | Sheskin, David J. 1941- |
| author_variant | d j s dj djs |
| building | Verbundindex |
| bvnumber | BV039574265 |
| classification_rvk | QH 230 SK 800 SK 830 |
| ctrlnum | (OCoLC)763124546 (DE-599)BVBBV039574265 |
| dewey-full | 519.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | 5. ed. |
| format | Book |
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| id | DE-604.BV039574265 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T00:06:34Z |
| institution | BVB |
| isbn | 9781439858011 1439858012 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-024425724 |
| oclc_num | 763124546 |
| open_access_boolean | |
| owner | DE-M382 DE-824 DE-19 DE-BY-UBM DE-29T DE-473 DE-BY-UBG DE-11 DE-83 DE-355 DE-BY-UBR DE-384 DE-634 DE-703 |
| owner_facet | DE-M382 DE-824 DE-19 DE-BY-UBM DE-29T DE-473 DE-BY-UBG DE-11 DE-83 DE-355 DE-BY-UBR DE-384 DE-634 DE-703 |
| physical | XXXIX, 1886 S. Ill., graph. Darst. 26 cm |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | CRC Press |
| record_format | marc |
| series2 | A Chapman & Hall book |
| spelling | Sheskin, David J. 1941- Verfasser (DE-588)1013718429 aut Handbook of parametric and nonparametric statistical procedures David J. Sheskin 5. ed. Boca Raton [u.a.] CRC Press 2011 XXXIX, 1886 S. Ill., graph. Darst. 26 cm txt rdacontent n rdamedia nc rdacarrier A Chapman & Hall book Includes bibliographical references and index Introduction -- Outline of inferential statistical tests and measures of correlation/association -- Guidelines and decision tables for selecting the appropriate statistical procedure -- Inferential statistical tests employed with a single sample -- Inferential statistical tests employed with two independent samples (and related measures of association/correlation) -- Inferential statistical tests employed with two or more independent samples (and related measures of association/correlation) -- Inferential statistical tests employed with two or more dependent samples (and related measures of association/correlation) -- Inferential statistical tests employed with a factorial design (and related measures of association/correlation) -- Measures of association/correlation -- Multivariate statistical analysis -- Appendix: Tables Mathematical statistics / Handbooks, manuals, etc Nichtparametrisches Verfahren (DE-588)4339273-8 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Statistische Schlussweise (DE-588)4182963-3 gnd rswk-swf Parametrisches Verfahren (DE-588)4205938-0 gnd rswk-swf Inferenzstatistik (DE-588)4247120-5 gnd rswk-swf Statistische Schlussweise (DE-588)4182963-3 s Parametrisches Verfahren (DE-588)4205938-0 s DE-604 Statistik (DE-588)4056995-0 s Nichtparametrisches Verfahren (DE-588)4339273-8 s Inferenzstatistik (DE-588)4247120-5 s 1\p DE-604 Digitalisierung UB Augsburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024425724&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Sheskin, David J. 1941- Handbook of parametric and nonparametric statistical procedures Mathematical statistics / Handbooks, manuals, etc Nichtparametrisches Verfahren (DE-588)4339273-8 gnd Statistik (DE-588)4056995-0 gnd Statistische Schlussweise (DE-588)4182963-3 gnd Parametrisches Verfahren (DE-588)4205938-0 gnd Inferenzstatistik (DE-588)4247120-5 gnd |
| subject_GND | (DE-588)4339273-8 (DE-588)4056995-0 (DE-588)4182963-3 (DE-588)4205938-0 (DE-588)4247120-5 |
| title | Handbook of parametric and nonparametric statistical procedures |
| title_auth | Handbook of parametric and nonparametric statistical procedures |
| title_exact_search | Handbook of parametric and nonparametric statistical procedures |
| title_full | Handbook of parametric and nonparametric statistical procedures David J. Sheskin |
| title_fullStr | Handbook of parametric and nonparametric statistical procedures David J. Sheskin |
| title_full_unstemmed | Handbook of parametric and nonparametric statistical procedures David J. Sheskin |
| title_short | Handbook of parametric and nonparametric statistical procedures |
| title_sort | handbook of parametric and nonparametric statistical procedures |
| topic | Mathematical statistics / Handbooks, manuals, etc Nichtparametrisches Verfahren (DE-588)4339273-8 gnd Statistik (DE-588)4056995-0 gnd Statistische Schlussweise (DE-588)4182963-3 gnd Parametrisches Verfahren (DE-588)4205938-0 gnd Inferenzstatistik (DE-588)4247120-5 gnd |
| topic_facet | Mathematical statistics / Handbooks, manuals, etc Nichtparametrisches Verfahren Statistik Statistische Schlussweise Parametrisches Verfahren Inferenzstatistik |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=024425724&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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