351 pages, Figs, tabs
Makes available to life science undergraduates methods such as model formulae and the General Linear Model, focusing on concepts such as marginality, random effects and multiplicity.
Why use this book; 1. An introduction to the analysis of variance; 2. Regression; 3. Models, parameters and GLMs; 4. Using more than one explanatory variable; 5. Designing experiments - keeping it simple; 6. Combining continuous and categorical variables; 7. Interactions - getting more complex; 8. Checking the models A: Independence; 9. Checking the models B: The other three assumptions; 10. Model selection I: Principles of model choice and designed experiments; 11. Model selection II: Data sets with several explanatory variables; 12. Random effects; 13. Categorical data; 14. What lies beyond?; Answers to exercises; Revision section: The basics; Appendix I: The meaning of p-values and confidence intervals; Appendix II: Analytical results about variances of sample means; Appendix III: Probability distributions; Bibliography
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