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This book provides a comprehensive treatment of the logic behind hypothesis testing. This updated edition covers frequentist (classical) and Bayesian approaches to interpretation of the results of a statistical hypothesis test. In a new chapter, nonparametric hypothesis testing is also discussed. The author describes the most commonly used statistical tests and provides instructions for how to perform them using Microsoft Office Excel. Readers will learn how to interpret P-values under a variety of conditions including a single hypothesis test, a collection of hypothesis tests, and tests performed on accumulating data. This new edition includes the chi-square test as a method for nominal data. The author provides frameworks for how to plan the size of a sample and how to select which test to use for a data set. This second edition will be of interest to researchers, graduate students, and anyone who has to interpret the results of statistical analyses.
Robert Hirsch, Ph.D., is the President of Stat-Aid Consulting. In 2010, he retired as Professor of Epidemiology and Biostatistics and Adjunct Professor of Statistics at The George Washington University, where he helped to develop the School of Public Health and Health Services. His main research interest is in relating statistics to real life problems, and much of his work has focused on applied mathematics for health research and practice.
Logic of Hypothesis Testing Classical (Frequentist) Approach Statistical Hypotheses and Conclusions.- Sampling.- Basic Statistical Methods Selecting a Test.- Nonparametric Methods.- Interim Analysis.- Planning the Sample's Size.
