3rd Edition

# Basic Statistics and Pharmaceutical Statistical Applications

By James E. De Muth Copyright 2014
848 Pages
by Chapman & Hall

848 Pages 262 B/W Illustrations
by Chapman & Hall

847 Pages
by Chapman & Hall

Also available as eBook on:

Building on its best-selling predecessors, Basic Statistics and Pharmaceutical Statistical Applications, Third Edition covers statistical topics most relevant to those in the pharmaceutical industry and pharmacy practice. It focuses on the fundamentals required to understand descriptive and inferential statistics for problem solving. Incorporating new material in virtually every chapter, this third edition now provides information on software applications to assist with evaluating data.

New to the Third Edition

• Use of Excel® and Minitab® for performing statistical analysis

• Discussions of nonprobability sampling procedures, determining if data is normally distributed, evaluation of covariances, and testing for precision equivalence

• Expanded sections on regression analysis, chi square tests, tests for trends with ordinal data, and tests related to survival statistics

• Additional nonparametric procedures, including the one-sided sign test, Wilcoxon signed-ranks test, and Mood’s median test

With the help of flow charts and tables, the author dispels some of the anxiety associated with using basic statistical tests in the pharmacy profession and helps readers correctly interpret their results using statistical software. Through the text’s worked-out examples, readers better understand how the mathematics works, the logic behind many of the equations, and the tests’ outcomes.

Introduction. Probability. Sampling. Presentation Modes. Measures of Central Tendency. The Normal Distribution and Data Transformation. Confidence Intervals and Tolerance Limits. Hypothesis Testing. T-Tests. One-Way Analysis of Variance. Multiple Comparison Tests. Factorial Designs: An Introduction. Correlation. Linear Regression. Z-Tests of Proportions. Chi Square Tests. Measures of Association. Odds Ratios and Relative Risk Ratios. Evidence Based Practice: An Introduction. Survival Statistics. Nonparametric Tests. Statistical Tests for Equivalence. Outlier Tests. Statistical Errors in the Literature. Appendices. Index.

### Biography

James E. De Muth

"The book’s coverage … is immense and very impressive. The book also well describes introductory statistics, and coverage of normal outcomes was exemplary. The multiple comparisons and nonparametric statistics chapters in particular were outstanding. The third edition has made notable improvements over the second edition in several chapters; there are too many to describe here. … very well written and easy to read. … very useful and unique reading, given its wide practical coverage and the approaches taken. I have added this book to my go-to reference sources … a very good teaching introduction to statistics for undergraduate and graduate students … This book may be most useful for persons involved in preclinical and Phase 1 studies where standard normal, binomial, and nonparametric methods are used."
Journal of Biopharmaceutical Statistics, 2015

Praise for the Second Edition:
"Dr. De Muth writes clearly about a very complex subject … The second edition has been expanded and is an even more comprehensive description of the statistics used within the pharmaceutical industry and the health care system. … a very useful reference tool for the pharmaceutical scientist and clinician…"
—Frank J. Ascione, University of Michigan College of Pharmacy

"De Muth has written a book that is both elegant and simple … [it] enables the reader to clearly understand how to appropriately use statistics in designing studies and just as importantly determine when statistics should not be used … an excellent reference book that will enable the non-statistician to appropriately use statistical approaches … A unique attribute of this statistical textbook is the acknowledgement of how statistical tests can be misused … useful information helps the non-statistician avoid some of the common errors that are made when using statistical approaches in the analysis of data."
—Mark N. Milton, Millennium Pharmaceuticals, Inc.

"The