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Analysis of Biological Data provides students with a practical foundation of statistics for biology students. Every chapter has several biological or medical examples of key concepts, and each example is prefaced by a substantial description of the biological setting. The emphasis on real and interesting examples carries into the problem sets where students have dozens of practice problems based on real data.
The third 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 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 adopting instructors.

The Analysis of Biological Data

PART 1 INTRODUCTION TO STATISTICS



1. Statistics and samples 1



INTERLEAF 1 Biology and the history of statistics 23



2. Displaying data 25



3. Describing data 65



4. Estimating with uncertainty 95



INTERLEAF 2 Pseudoreplication 115



5. Probability 117



6. Hypothesis testing 149



INTERLEAF 3 Why statistical significance is not the same



as biological importance 176



PART 2 PROPORTIONS AND FREQUENCIES



7. Analyzing proportions 179



INTERLEAF 4 Correlation does not require causation 201



8. Fitting probability models to frequency data 203



INTERLEAF 5 Making a plan 233



9. Contingency analysis: associations between



categorical variables 235



Review Problems 1 269



vii



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viii Contents in brief



PART 3 COMPARING NUMERICAL VALUES



10. The normal distribution 273



INTERLEAF 6 Controls in medical studies 301



11. Inference for a normal population 303



12. Comparing two means 327



INTERLEAF 7 Which test should I use? 366



13. Handling violations of assumptions 369



Review Problems 2 417



14. Designing experiments 423



INTERLEAF 8 Data dredging 456



15. Comparing means of more than two groups 459



INTERLEAF 9 Experimental and statistical mistakes 500



PART 4 REGRESSION AND CORRELATION



16. Correlation between numerical variables 503



INTERLEAF 10 Publication bias 535



17. Regression 539



INTERLEAF 11 Using species as data points 593



Review Problems 3 597



PART 5 MODERN STATISTICAL METHODS



18. Multiple explanatory variables 605



19. Computer-intensive methods 635



20. Likelihood 655



21. Meta-analysis: combining information from



multiple studies 681