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Statistical hypothesis testing with SAS and R / 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 Univeristy of Applied Sciences and Arts, Dortmund, Germany.

By: Contributor(s): Material type: TextTextPublisher: Chichester, West Sussex : Wiley, 2014Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118762615
  • 1118762614
  • 9781118762608
  • 1118762606
  • 9781118762585
  • 1118762584
Subject(s): Genre/Form: Additional physical formats: Print version:: Statistical hypothesis testing with SAS and R.DDC classification:
  • 519.50285/5133 23
LOC classification:
  • QA277
Other classification:
  • MAT029000
Online resources:
Contents:
Cover; Title Page; Copyright; Contents; Preface; Part I Introduction; Chapter 1 Statistical hypothesis testing; 1.1 Theory of statistical hypothesis testing; 1.2 Testing statistical hypothesis with SAS and R; 1.2.1 Programming philosophy of SAS and R; 1.2.2 Testing in SAS and R-An example; 1.2.3 Calculating p-values; 1.3 Presentation of the statistical tests; References; Part II Normal Distribution; Chapter 2 Tests on the mean; 2.1 One-sample tests; 2.1.1 z-test; 2.1.2 t-test; 2.2 Two-sample tests; 2.2.1 Two-sample z-test; 2.2.2 Two-sample pooled t-test; 2.2.3 Welch test; 2.2.4 Paired z-test.
2.2.5 Paired t-testReferences; Chapter 3 Tests on the variance; 3.1 One-sample tests; 3.1.1 x2-test on the variance (mean known); 3.1.2 x2-test on the variance (mean unknown); 3.2 Two-sample tests; 3.2.1 Two-sample F-test on variances of two populations; 3.2.2 t-test on variances of two dependent populations; References; Part III Binomial Distribution; Chapter 4 Tests on proportions; 4.1 One-sample tests; 4.1.1 Binomial test; 4.2 Two-sample tests; 4.2.1 z-test for the difference of two proportions (unpooled variances); 4.2.2 z-test for the equality between two proportions (pooled variances).
4.3 K-sample tests4.3.1 K-sample binomial test; References; Part IV Other Distributions; Chapter 5 Poisson distribution; 5.1 Tests on the Poisson parameter; 5.1.1 z-test on the Poisson parameter; 5.1.2 Exact test on the Poisson parameter; 5.1.3 z-test on the difference between two Poisson parameters; References; Chapter 6 Exponential distribution; 6.1 Test on the parameter of an exponential distribution; 6.1.1 z-test on the parameter of an exponential distribution; Reference; Part V Correlation; Chapter 7 Tests on association; 7.1 One-sample tests.
7.1.1 Pearson's product moment correlation coefficient7.1.2 Spearman's rank correlation coefficient; 7.1.3 Partial correlation; 7.2 Two-sample tests; 7.2.1 z-test for two correlation coefficients (independent populations); References; Part VI Nonparametric Tests; Chapter 8 Tests on location; 8.1 One-sample tests; 8.1.1 Sign test; 8.1.2 Wilcoxon signed-rank test; 8.2 Two-sample tests; 8.2.1 Wilcoxon rank-sum test (Mann-Whitney U test); 8.2.2 Wilcoxon matched-pairs signed-rank test; 8.3 K-sample tests; 8.3.1 Kruskal-Wallis test; References; Chapter 9 Tests on scale difference.
9.1 Two-sample tests9.1.1 Siegel-Tukey test; 9.1.2 Ansari-Bradley test; 9.1.3 Mood test; References; Chapter 10 Other tests; 10.1 Two-sample tests; 10.1.1 Kolmogorov-Smirnov two-sample test (Smirnov test); References; Part VII Goodness-of-Fit Tests; Chapter 11 Tests on normality; 11.1 Tests based on the EDF; 11.1.1 Kolmogorov-Smirnov test (Lilliefors test for normality); 11.1.2 Anderson-Darling test; 11.1.3 Cramér-von Mises test; 11.2 Tests not based on the EDF; 11.2.1 Shapiro-Wilk test; 11.2.2 Jarque-Bera test; References; Chapter 12 Tests on other distributions; 12.1 Tests based on the EDF.
Summary: "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"-- Provided by publisher.Summary: "Presents a comprehensive guide to hypothesis testing using SAS and R"-- Provided by publisher.
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"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"-- Provided by publisher.

"Presents a comprehensive guide to hypothesis testing using SAS and R"-- Provided by publisher.

Includes bibliographical references and index.

Print version record and CIP data provided by publisher.

Cover; Title Page; Copyright; Contents; Preface; Part I Introduction; Chapter 1 Statistical hypothesis testing; 1.1 Theory of statistical hypothesis testing; 1.2 Testing statistical hypothesis with SAS and R; 1.2.1 Programming philosophy of SAS and R; 1.2.2 Testing in SAS and R-An example; 1.2.3 Calculating p-values; 1.3 Presentation of the statistical tests; References; Part II Normal Distribution; Chapter 2 Tests on the mean; 2.1 One-sample tests; 2.1.1 z-test; 2.1.2 t-test; 2.2 Two-sample tests; 2.2.1 Two-sample z-test; 2.2.2 Two-sample pooled t-test; 2.2.3 Welch test; 2.2.4 Paired z-test.

2.2.5 Paired t-testReferences; Chapter 3 Tests on the variance; 3.1 One-sample tests; 3.1.1 x2-test on the variance (mean known); 3.1.2 x2-test on the variance (mean unknown); 3.2 Two-sample tests; 3.2.1 Two-sample F-test on variances of two populations; 3.2.2 t-test on variances of two dependent populations; References; Part III Binomial Distribution; Chapter 4 Tests on proportions; 4.1 One-sample tests; 4.1.1 Binomial test; 4.2 Two-sample tests; 4.2.1 z-test for the difference of two proportions (unpooled variances); 4.2.2 z-test for the equality between two proportions (pooled variances).

4.3 K-sample tests4.3.1 K-sample binomial test; References; Part IV Other Distributions; Chapter 5 Poisson distribution; 5.1 Tests on the Poisson parameter; 5.1.1 z-test on the Poisson parameter; 5.1.2 Exact test on the Poisson parameter; 5.1.3 z-test on the difference between two Poisson parameters; References; Chapter 6 Exponential distribution; 6.1 Test on the parameter of an exponential distribution; 6.1.1 z-test on the parameter of an exponential distribution; Reference; Part V Correlation; Chapter 7 Tests on association; 7.1 One-sample tests.

7.1.1 Pearson's product moment correlation coefficient7.1.2 Spearman's rank correlation coefficient; 7.1.3 Partial correlation; 7.2 Two-sample tests; 7.2.1 z-test for two correlation coefficients (independent populations); References; Part VI Nonparametric Tests; Chapter 8 Tests on location; 8.1 One-sample tests; 8.1.1 Sign test; 8.1.2 Wilcoxon signed-rank test; 8.2 Two-sample tests; 8.2.1 Wilcoxon rank-sum test (Mann-Whitney U test); 8.2.2 Wilcoxon matched-pairs signed-rank test; 8.3 K-sample tests; 8.3.1 Kruskal-Wallis test; References; Chapter 9 Tests on scale difference.

9.1 Two-sample tests9.1.1 Siegel-Tukey test; 9.1.2 Ansari-Bradley test; 9.1.3 Mood test; References; Chapter 10 Other tests; 10.1 Two-sample tests; 10.1.1 Kolmogorov-Smirnov two-sample test (Smirnov test); References; Part VII Goodness-of-Fit Tests; Chapter 11 Tests on normality; 11.1 Tests based on the EDF; 11.1.1 Kolmogorov-Smirnov test (Lilliefors test for normality); 11.1.2 Anderson-Darling test; 11.1.3 Cramér-von Mises test; 11.2 Tests not based on the EDF; 11.2.1 Shapiro-Wilk test; 11.2.2 Jarque-Bera test; References; Chapter 12 Tests on other distributions; 12.1 Tests based on the EDF.

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