BookAlan Grafen, Rosie Hails.
Summary: Model formulae represent a powerful methodology for describing, discussing, understanding, and performing that large part of statistical tests known as linear statistics. The book aims to put this methodology firmly within the grasp of undergraduates.
Contents:
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.
Location
Version
Call Number
Items