The Analysis of Biological Data

Knowledge of statistics is essential in modern biology and medicine. Biologists and health professionals learn statistics best with real and interesting examples. The Analysis of Biological Data, Second Edition, by Whitlock and Schluter, teaches modern methods of statistics through the use of fascinating biological and medical cases. Readers consistently praise its clear and engaging writing and practical perspective.

The second edition features over 200 new examples and problems. These include new calculation practice problems, which guide the student step by step through the methods, and a greater number of the examples and topics come from medical and human health research.  Every chapter has been carefully edited for even greater clarity and ease of use. All the data sets, R scripts for all worked examples in the book, as well as many other teaching resources, are available to qualified instructors (see below).

The Analysis of Biological Data is the most widely adopted introductory biological statistics textbook. It is now used at well over 200 schools and on every continent.

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