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E-raamat: Statistical Hypothesis Testing with SAS and R [Wiley Online]

(TU Dortmund University), (Institute for Prevention)
  • Formaat: 312 pages
  • Ilmumisaeg: 12-Mar-2014
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1118762584
  • ISBN-13: 9781118762585
Teised raamatud teemal:
  • Wiley Online
  • Hind: 106,73 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
Statistical Hypothesis Testing with SAS and RSuurem pilt
  • Formaat: 312 pages
  • Ilmumisaeg: 12-Mar-2014
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1118762584
  • ISBN-13: 9781118762585
Teised raamatud teemal:
Wiley Online e-raamatudRohkem infot Wiley Online kohta
Raamatu kodulehekülg: https://onlinelibrary.wiley.com/doi/book/10.1002/9781118762585
"This book provides a reference guide to statistical tests and their application to data using SAS and R. A general summary of statistical test theory is presented, along with a general description for each test, together with necessary prerequisites, assumptions, and the formal test problem. The test statistic is stated together with annotations on its distribution, along with examples in both SAS and R. Each example contains the code to perform the test, the output, and remarks that explain necessary program parameters"--

"Presents a comprehensive guide to hypothesis testing using SAS and R"--

Taeger and Kuhnt present an overview of common statistical tests and how to apply them using two popular statistical software packages. For each test, they provide a general description and the necessary prerequisites, assumptions, and the formal test problem; and state the test statistic along with annotations on its distribution. Two examples--one in SAS and one in R--present the code to perform the test using a tiny dataset, and include output and remarks that explain necessary program parameters. Undergraduate and graduate students, researchers, and practitioners could use the book as a reference. Annotation ©2014 Ringgold, Inc., Portland, OR (protoview.com)

This book provides a reference guide to statistical tests and their application to data using SAS and R. A general summary of statistical test theory is presented, along with a general description for each test, together with necessary prerequisites, assumptions, and the formal test problem.

A comprehensive guide to statistical hypothesis testing with examples in SAS and R

When analyzing datasets the following questions often arise:

Is there a short hand procedure for a statistical test available in SAS or R?
If so, how do I use it?
If not, how do I program the test myself?

This book answers these questions and provides an overview of the most common
statistical test problems in a comprehensive way, making it easy to find and perform
an appropriate statistical test.

A general summary of statistical test theory is presented, along with a basic
description for each test, including the necessary prerequisites, assumptions, the
formal test problem and the test statistic. Examples in both SAS and R are provided,
along with program code to perform the test, resulting output and remarks
explaining the necessary program parameters.

Key features:
• Provides examples in both SAS and R for each test presented.
• Looks at the most common statistical tests, displayed in a clear and easy to follow way.
• Supported by a supplementary website http://www.d-taeger.de featuring example
program code.

Academics, practitioners and SAS and R programmers will find this book a valuable
resource. Students using SAS and R will also find it an excellent choice for reference
and data analysis.

Preface xiii
Part I INTRODUCTION
1(16)
1 Statistical hypothesis testing
3(14)
1.1 Theory of statistical hypothesis testing
3(1)
1.2 Testing statistical hypothesis with SAS and R
4(9)
1.2.1 Programming philosophy of SAS and R
5(1)
1.2.2 Testing in SAS and R--An example
6(5)
1.2.3 Calculating p-values
11(2)
1.3 Presentation of the statistical tests
13(4)
References
15(2)
Part II NORMAL DISTRIBUTION
17(32)
2 Tests on the mean
19(17)
2.1 One-sample tests
19(4)
2.1.1 z-test
19(3)
2.1.2 t-test
22(1)
2.2 Two-sample tests
23(13)
2.2.1 Two-sample z-test
23(3)
2.2.2 Two-sample pooled t-test
26(2)
2.2.3 Welch test
28(3)
2.2.4 Paired z-test
31(2)
2.2.5 Paired t-test
33(2)
References
35(1)
3 Tests on the variance
36(13)
3.1 One-sample tests
36(5)
3.1.1 Χ-test on the variance (mean known)
36(3)
3.1.2 Χ2-test on the variance (mean unknown)
39(2)
3.2 Two-sample tests
41(8)
3.2.1 Two-sample F-test on variances of two populations
41(3)
3.2.2 t-test on variances of two dependent populations
44(3)
References
47(2)
Part III BINOMIAL DISTRIBUTION
49(16)
4 Tests on proportions
51(14)
4.1 One-sample tests
51(4)
4.1.1 Binomial test
51(4)
4.2 Two-sample tests
55(7)
4.2.1 z-test for the difference of two proportions (unpooled variances)
55(4)
4.2.2 z-test for the equality between two proportions (pooled variances)
59(3)
4.3 K-sample tests
62(3)
4.3.1 K-sample binomial test
62(2)
References
64(1)
Part IV OTHER DISTRIBUTIONS
65(14)
5 Poisson distribution
67(9)
5.1 Tests on the Poisson parameter
67(9)
5.1.1 z-test on the Poisson parameter
67(3)
5.1.2 Exact test on the Poisson parameter
70(2)
5.1.3 z-test on the difference between two Poisson parameters
72(3)
References
75(1)
6 Exponential distribution
76(3)
6.1 Test on the parameter of an exponential distribution
76(3)
6.1.1 z-test on the parameter of an exponential distribution
76(2)
Reference
78(1)
Part V CORRELATION
79(20)
7 Tests on association
81(18)
7.1 One-sample tests
81(13)
7.1.1 Pearson's product moment correlation coefficient
81(5)
7.1.2 Spearman's rank correlation coefficient
86(5)
7.1.3 Partial correlation
91(3)
7.2 Two-sample tests
94(5)
7.2.1 z-test for two correlation coefficients (independent populations)
94(4)
References
98(1)
Part VI NONPARAMETRIC TESTS
99(38)
8 Tests on location
101(19)
8.1 One-sample tests
101(9)
8.1.1 Sign test
101(4)
8.1.2 Wilcoxon signed-rank test
105(5)
8.2 Two-sample tests
110(6)
8.2.1 Wilcoxon rank-sum test (Mann--Whitney U test)
110(4)
8.2.2 Wilcoxon matched-pairs signed-rank test
114(2)
8.3 K-sample tests
116(4)
8.3.1 Kruskal--Wallis test
116(2)
References
118(2)
9 Tests on scale difference
120(12)
9.1 Two-sample tests
120(12)
9.1.1 Siegel--Tukey test
120(5)
9.1.2 Ansari--Bradley test
125(3)
9.1.3 Mood test
128(3)
References
131(1)
10 Other tests
132(5)
10.1 Two-sample tests
132(5)
10.1.1 Kolmogorov--Smirnov two-sample test (Smirnov test)
132(3)
References
135(2)
Part VII GOODNESS-OF-FIT TESTS
137(30)
11 Tests on normality
139(15)
11.1 Tests based on the EDF
139(9)
11.1.1 Kolmogorov--Smirnov test (Lilliefors test for normality)
139(3)
11.1.2 Anderson--Darling test
142(3)
11.1.3 Cramer--von Mises test
145(3)
11.2 Tests not based on the EDF
148(6)
11.2.1 Shapiro--Wilk test
148(2)
11.2.2 Jarque--Bera test
150(2)
References
152(2)
12 Tests on other distributions
154(13)
12.1 Tests based on the EDF
154(10)
12.1.1 Kolmogorov--Smirnov test
154(3)
12.1.2 Anderson--Darling test
157(3)
12.1.3 Cramer--von Mises test
160(4)
12.2 Tests not based on the EDF
164(3)
12.2.1 Χ2 Goodness-of-fit test
164(2)
References
166(1)
Part VIII TESTS ON RANDOMNESS
167(20)
13 Tests on randomness
169(18)
13.1 Run tests
169(9)
13.1.1 Wald--Wolfowitz runs test
169(5)
13.1.2 Runs up and down test
174(4)
13.2 Successive difference tests
178(9)
13.2.1 von Neumann test
178(3)
13.2.2 von Neumann rank test (Bartels' test)
181(4)
References
185(2)
Part IX TESTS ON CONTINGENCY TABLES
187(30)
14 Tests on contingency tables
189(28)
14.1 Tests on independence and homogeneity
189(8)
14.1.1 Fisher's exact test
189(3)
14.1.2 Pearson's Χ2-test
192(3)
14.1.3 Likelihood-ratio Χ2-test
195(2)
14.2 Tests on agreement and symmetry
197(8)
14.2.1 Test on Cohen's kappa
197(3)
14.2.2 McNemar's test
200(3)
14.2.3 Bowker's test for symmetry
203(2)
14.3 Test on risk measures
205(12)
14.3.1 Large sample test on the odds ratio
205(5)
14.3.2 Large sample test on the relative risk
210(4)
References
214(3)
Part X TESTS ON OUTLIERS
217(20)
15 Tests on outliers
219(18)
15.1 Outliers tests for Gaussian null distribution
219(10)
15.1.1 Grubbs' test
219(4)
15.1.2 David--Hartley--Pearson test
223(2)
15.1.3 Dixon's tests
225(4)
15.2 Outlier tests for other null distributions
229(8)
15.2.1 Test on outliers for exponential null distributions
229(3)
15.2.2 Test on outliers for uniform null distributions
232(3)
References
235(2)
Part XI TESTS IN REGRESSION ANALYSIS
237(27)
16 Tests in regression analysis
239(14)
16.1 Simple linear regression
239(7)
16.1.1 Test on the slope
239(4)
16.1.2 Test on the intercept
243(3)
16.2 Multiple linear regression
246(7)
16.2.1 Test on an individual regression coefficient
247(3)
16.2.2 Test for significance of regression
250(2)
References
252(1)
17 Tests in variance analysis
253(11)
17.1 Analysis of variance
253(5)
17.1.1 One-way ANOVA
253(2)
17.1.2 Two-way ANOVA
255(3)
17.2 Tests for homogeneity of variances
258(6)
17.2.1 Bartlett test
258(2)
17.2.2 Levene test
260(3)
References
263(1)
Appendix A Datasets 264(7)
Appendix B Tables 271(13)
Glossary 284(3)
Index 287
Dirk Taeger, Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr-Universität Bochum (IPA), Bochum, Germany

Sonja Kuhnt, Department of Computer Science, Dortmund University of Applied Sciences and Arts, Dortmund, Germany
Püsilink: https://www.kriso.ee/db/9781118762585_pe.html
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