
Modern Analysis of Biological Data
Generalized Linear Models in R
- English
- PDF
- Available on iOS & Android
About this book
The book is focused on regression models, specifically generalized linear models (GLM). It is intended for biology students and scholars and requires only basic statistical knowledge, gained e.g. in an one-semester course of biostatistics. The text includes a minimum of statistical theory and eighteen real examples from biology. Each example consists of a description of a problem, aims, development of statistical models, analysis, diagnosis, and conclusion. Analysis is performed using R. All examples were selected to show a variety of problems and potential pitfalls that can arise during statistical analysis. At the same time, examples show how to think about the statistical models and how to use them. Analyses can be practised by readers using the data that come with the book.
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Information
Table of contents
- CONTENTS
- FOREWORD
- 1 INTRODUCTION
- 2 STATISTICAL SOFTWARE
- 3 EXPLORATORY DATA ANALYSIS (EDA)
- 4 STATISTICAL MODELLING
- 5 THE FIRST TRIAL
- 6 SYSTEMATIC PART
- 7 RANDOM PART
- 8 GAUSSIAN DISTRIBUTION
- 9 GAMMA AND LOGNORMAL DISTRIBUTIONS
- 10 POISSON DISTRIBUTION
- 11 NEGATIVE-BINOMIAL DISTRIBUTION
- 12 BINOMIAL DISTRIBUTION
- REFERENCES
- INDEX