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With its engaging and conversational tone, Essential Biostatistics: A Nonmathematical Approach provides a clear introduction to statistics for students in a wide range of fields, and a concise statistics refresher for scientists and professionals who need to interpret statistical results. It explains the ideas behind statistics in nonmathematical terms, offers perspectives on how to interpret published statistical results, and points out common conceptual traps to avoid. It can be used as a stand-alone text or as a supplement to a traditional statistics textbook.
1. Statistics and Probability Are Not Intuitive
2. The Complexities of Probability
3. From Sample to Population
4. Confidence Intervals
5. Types of Variables
6. Graphing Variability
7. Quantifying Variation
8. The Gaussian Distribution
9. The Lognormal Distribution and Geometric Mean
10. Confidence Interval for a Mean
11. Error Bars
12. Comparing Groups with Confidence Intervals
13. Comparing Groups with P Values
14. Statistical Significance and Hypothesis Testing
15. Interpreting a Result that Is (Or Is Not) Statistically Significant
16. How Common Are Type I Errors?
17. Multiple Comparisons
18. Statistical Power and Sample Size
19. Commonly Used Statistical Tests
20. Normality Tests
21. Outliers
22. Correlation
23. Simple Linear Regression
24. Nonlinear Regression
25. Multiple and Logistic Regression
26. Summary: The Key Concepts of Statistics
27. Statistical Traps to Avoid
References
Index
Harvey Motulsky is the founder and CEO of GraphPad Software, Inc.
"Essential Biostatistics distills the essence of university-level biostatistics topics in accessible, concise language that is engaging and thought-provoking. This text would be an excellent companion to a traditional biostatistics book."
– Derek Webb, Bemidji State University
"The author does a great job explaining why we use statistics rather than getting bogged down explaining how we calculate statistics. I find it refreshing to step back from the calculations to see the larger context of why we use statistics in science."
– Dean W. Coble, Stephen F. Austin State University
"I really like the clear and humorous style, the wealth of examples, and the discussions of the limits and pitfalls. This is a wonderful book."
– Naji Younes, George Washington University
