Modern statistics for the life sciences/
Alan Grafen and Rosie Hails
- Oxford: Oxford University Press, 2008.
- xv, 351 p. : ill. ; 25 cm.
1. Introduction to 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 I: independence -- 9. Checking the models II: the other three asumptions -- 10. Model selection I: principles of model choice and designed experiments -- 11. Model selection II: datasets with several explanatory variables -- 12. Random effects -- 13. Categorical data -- 14. What lies beyond? -- 15. Answers to exercises -- App. 1. meaning of p-values and confidence intervals -- App. 2. Analytical results about variances and sample means -- App. 3. Probability distributions.
9780199252312
Mathematical statistics Life sciences--Statistical methods