Introductory Statistics for the Health Sciences takes students on a journey to a wilderness where science explores the unknown, providing students with a strong, practical foundation in statistics. Using a color format throughout, the book contains engaging figures that illustrate real data sets from published research. Examples come from many areas of the health sciences, including medicine, nursing, pharmacy, dentistry, and physical therapy, but are understandable to students in any field. The book can be used in a first-semester course in a health sciences program or in a service course for undergraduate students who plan to enter a health sciences program.
The book begins by explaining the research context for statistics in the health sciences, which provides students with a framework for understanding why they need statistics as well as a foundation for the remainder of the text. It emphasizes kinds of variables and their relationships throughout, giving a substantive context for descriptive statistics, graphs, probability, inferential statistics, and interval estimation. The final chapter organizes the statistical procedures in a decision tree and leads students through a process of assessing research scenarios.
The authors have partnered with William Howard Beasley, who created the illustrations in the book, to offer all of the data sets, graphs, and graphing code in an online data repository via GitHub. A dedicated website gives information about the data sets and the authors’ electronic flashcards for iOS and Android devices. These flashcards help students learn new terms and concepts.
Table of Contents
The Frontier between Knowledge and Ignorance. Describing Distributions with Statistics: Middle, Spread, and Skewness. Exploring Data Visually. Relative Location and Normal Distributions. Bivariate Correlation. Probability and Risk. Sampling Distributions and Estimation. Hypothesis Testing and Interval Estimation. Types of Errors and Power. One-Sample Tests and Estimates. Two-Sample Tests and Estimates. Tests and Estimates for Two or More Samples. Tests and Estimates for Bivariate Linear Relationships. Analysis of Frequencies and Ranks. Choosing an Analysis Plan. Suggested Answers to Odd-Numbered Exercises. Appendix. Index.
Lise DeShea is the senior research biostatistician in the College of Nursing at the University of Oklahoma Health Sciences Center. She has served on the faculty of the University of Kentucky and worked as a statistician for a Medicaid agency. She has conducted research on emergency room utilization, bootstrapping, and forgiveness.
Larry E. Toothaker is an emeritus David Ross Boyd Professor, the highest honor for teaching excellence at the University of Oklahoma. He has conducted research on multiple comparison procedures and nonparametric methods. He retired in 2008 after teaching statistics in the Department of Psychology for 40 years.
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