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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 plus SaplingPlus Pack

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