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A concise, engagingly written introduction to understanding statistics as they apply to medicine and the life sciences
Don't be afraid of biostatistics anymore! Primer of Biostatistics, 7th edition demystifies this challenging topic in an interesting and enjoyable manner that assumes no prior knowledge of the subject. Faster than you thought possible, you'll understand test selection and be able to evaluate biomedical statistics critically, knowledgeably, and confidently.
With Primer of Biostatistics, you'll start with the basics, including analysis of variance and the t test, then advance to multiple comparison testing, contingency tables, regression, and more. Illustrative examples and challenging problems, culled from the recent biomedical literature, highlight the discussions throughout and help to foster a more intuitive approach to biostatistics. The companion CD-ROM contains everything you need to run thirty statistical tests of your own data. Review questions and summaries in each chapter facilitate the learning process and help you gauge your comprehension. By combining whimsical studies of Martians and other planetary residents with actual papers from the biomedical literature, the author makes the subject fun and enjoyable.
COVERAGE INCLUDES:
How to summarize data
How to test for differences between groups
The t test
How to analyze rates and proportions
What does "not significant" really mean?
Confidence intervals
How to test for trends
Experiments when each subject receives more than one treatment
Alternatives to analysis of variance and the t test based on ranks
How to analyze survival data
CD-ROM PERFORMS 30 STATISTICAL TESTS
List of contents
Preface
1. Biostatistics and Clinical Practice
2. How to Summarize Data
3. How to Test for Differences between Groups
4. The Special Case of Two Groups: The t test
5. How to Analyze Rates and Proportions
6. What Does "Not Significant" Really Mean?
7. Confidence Intervals
8. How to Test for Trends
9. Experiments When Each Subject Receives More Than One Treatment
10. Alternatives to Analysis of Variance and the t test Based on Ranks
11. How to Analyze Survival Data
12. What Do the Data Really Show?
Appendix A: Computational Forms
Appendix B: Statistical Tables and Power Charts
Appendix C: Answers to Exercises
Index
About the author
Stanton A. Glantz, PhD, Professor of Medicine, also Member, Cardiovascular Research Institute, Institute for Health Policy Studies, and Cancer Center, University of California, San Francisco.
Summary
Features an introduction to understanding statistics as they apply to medicine and the life sciences. This is an analysis of variance and the t test, then advance to multiple comparison testing, contingency tables, regression, and more.
