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Full Description
This textbook teaches statistics in a different way. It is aimed at undergraduate students in the life sciences, and it will also be invaluable for many graduate students. It makes the powerful methods of model formulae and the General Linear Model accessible to undergraduates for the first time. The computer revolution has finally made it possible to teach life sciences undergraduates how to use the statistics they really need to know - this book provides the course materials needed to fulfil that possibility. This text presents the fundamental statistical concepts without being tied to any one statistical package. Three supplements available on the web site provide all the information you need to conduct the analyses in either Minitab, SAS, or SPSS. All datasets are available on the web site.
Contents
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
