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 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.
Author(s): Dirk Taeger, Sonja Kuhnt
Publisher: Wiley&Sons
Year: 2014
Language: English
Commentary: TruePDF
Pages: 308
Tags: Statistical Hypothesis Testing
Cover......Page 1
Title Page......Page 5
Copyright......Page 6
Contents......Page 9
Preface......Page 15
Part I Introduction......Page 17
1.1 Theory of statistical hypothesis testing......Page 19
1.2 Testing statistical hypothesis with SAS and R......Page 20
1.2.1 Programming philosophy of SAS and R......Page 21
1.2.2 Testing in SAS and R-An example......Page 22
1.2.3 Calculating p-values......Page 27
1.3 Presentation of the statistical tests......Page 29
References......Page 31
Part II Normal Distribution......Page 33
2.1.1 z-test......Page 35
2.1.2 t-test......Page 38
2.2.1 Two-sample z-test......Page 39
2.2.2 Two-sample pooled t-test......Page 42
2.2.3 Welch test......Page 44
2.2.4 Paired z-test......Page 47
2.2.5 Paired t-test......Page 49
References......Page 51
3.1.1 x2-test on the variance (mean known)......Page 52
3.1.2 x2-test on the variance (mean unknown)......Page 55
3.2.1 Two-sample F-test on variances of two populations......Page 57
3.2.2 t-test on variances of two dependent populations......Page 60
References......Page 63
Part III Binomial Distribution......Page 65
4.1.1 Binomial test......Page 67
4.2.1 z-test for the difference of two proportions (unpooled variances)......Page 71
4.2.2 z-test for the equality between two proportions (pooled variances)......Page 75
4.3.1 K-sample binomial test......Page 78
References......Page 80
Part IV Other Distributions......Page 81
5.1.1 z-test on the Poisson parameter......Page 83
5.1.2 Exact test on the Poisson parameter......Page 86
5.1.3 z-test on the difference between two Poisson parameters......Page 88
References......Page 91
6.1.1 z-test on the parameter of an exponential distribution......Page 92
Reference......Page 94
Part V Correlation......Page 95
7.1.1 Pearson's product moment correlation coefficient......Page 97
7.1.2 Spearman's rank correlation coefficient......Page 102
7.1.3 Partial correlation......Page 107
7.2.1 z-test for two correlation coefficients (independent populations)......Page 110
References......Page 114
Part VI Nonparametric Tests......Page 115
8.1.1 Sign test......Page 117
8.1.2 Wilcoxon signed-rank test......Page 121
8.2.1 Wilcoxon rank-sum test (Mann-Whitney U test)......Page 126
8.2.2 Wilcoxon matched-pairs signed-rank test......Page 130
8.3.1 Kruskal-Wallis test......Page 132
References......Page 134
9.1.1 Siegel-Tukey test......Page 136
9.1.2 Ansari-Bradley test......Page 141
9.1.3 Mood test......Page 144
References......Page 147
10.1.1 Kolmogorov-Smirnov two-sample test (Smirnov test)......Page 148
References......Page 151
Part VII Goodness-of-Fit Tests......Page 153
11.1.1 Kolmogorov-Smirnov test (Lilliefors test for normality)......Page 155
11.1.2 Anderson-Darling test......Page 158
11.1.3 Cramér-von Mises test......Page 161
11.2.1 Shapiro-Wilk test......Page 164
11.2.2 Jarque-Bera test......Page 166
References......Page 168
12.1.1 Kolmogorov-Smirnov test......Page 170
12.1.2 Anderson-Darling test......Page 173
12.1.3 Cramér-von Mises test......Page 176
12.2.1 x2-Goodness-of-fit test......Page 180
References......Page 182
Part VIII Tests on Randomness......Page 183
13.1.1 Wald-Wolfowitz runs test......Page 185
13.1.2 Runs up and down test......Page 190
13.2.1 von Neumann test......Page 194
13.2.2 von Neumann rank test (Bartels' test)......Page 197
References......Page 201
Part IX Tests on Contingency Tables......Page 203
14.1.1 Fisher's exact test......Page 205
14.1.2 Pearson's x2-test......Page 208
14.1.3 Likelihood-ratio x2-test......Page 211
14.2.1 Test on Cohen's kappa......Page 213
14.2.2 McNemar's test......Page 216
14.2.3 Bowker's test for symmetry......Page 219
14.3.1 Large sample test on the odds ratio......Page 221
14.3.2 Large sample test on the relative risk......Page 226
References......Page 230
Part X Tests on Outliers......Page 233
15.1.1 Grubbs' test......Page 235
15.1.2 David-Hartley-Pearson test......Page 239
15.1.3 Dixon's tests......Page 241
15.2.1 Test on outliers for exponential null distributions......Page 245
15.2.2 Test on outliers for uniform null distributions......Page 248
References......Page 251
Part XI Tests in Regression Analysis......Page 253
16.1.1 Test on the slope......Page 255
16.1.2 Test on the intercept......Page 259
16.2 Multiple linear regression......Page 262
16.2.1 Test on an individual regression coefficient......Page 263
16.2.2 Test for significance of regression......Page 266
References......Page 268
17.1.1 One-way ANOVA......Page 269
17.1.2 Two-way ANOVA......Page 271
17.2.1 Bartlett test......Page 274
17.2.2 Levene test......Page 276
References......Page 279
Appendix A Datasets......Page 280
Appendix B Tables......Page 287
Glossary......Page 300
Index......Page 303
