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This second edition textbook teaches modern methods of statistics through the use of fascinating biological and medical case studies. The clear and engaging writing and practical perspective allows students to understand the analytical process behind biological data. Through the use of real world biological examples, biologists and health professionals can learn statistics in an essential manner.
Authors Whitlock and Schulter have over 40 years' experience between the two of them and therefore able to understand that students learn best through interesting examples and not overcomplicated formulas. This edition includes several unusual features that they have discovered to be helpful for effectively reaching their readers.

The Analysis of Biological Data

PART 1. INTRODUCTION TO STATISTICS.- 1. Statistics and samples .- INTERLEAF 1 Biology and the history of statistics .- 2. Displaying data.- 3. Describing data .- 4. Estimating with uncertainty .- INTERLEAF 2 Pseudoreplication .- 5. Probability .- 6. Hypothesis testing .- INTERLEAF 3 Why statistical significance is not the same as biological importance .- PART 2. PROPORTIONS AND FREQUENCIES
7. Analyzing proportions .- INTERLEAF 4 Correlation does not require causation .- 8. Fitting probability models to frequency data .- INTERLEAF 5 Making a plan .- 9. Contingency analysis: associations between categorical variables .- PART 3. COMPARING NUMERICAL VALUES.- 10. The normal distribution .- INTERLEAF 6 Controls in medical studies .- 11. Inference for a normal population .- 12. Comparing two means .- INTERLEAF 7 Which test should I use? .- 13. Handling violations of assumptions.- 14. Designing experiments .- INTERLEAF 8 Data dredging.- 15. Comparing means of more than two groups .- INTERLEAF 9 Experimental and statistical mistakes .- PART 4. REGRESSION AND CORRELATION.- 16. Correlation between numerical variables .- INTERLEAF 10 Publication bias
17. Regression .- INTERLEAF 11 Using species as data points .- PART 5. MODERN STATISTICAL METHODS.- 18. Multiple explanatory variables .- 19. Computer-intensive methods .- 20. Likelihood .- 21. Meta-analysis: combining information from multiple studies.- Answers to practice problems .- Literature cited.- Statistical tables .- Photo credits .- Index.