Statistical Methods in Biology: Design and Analysis of Experiments and Regression

Content: Introduction. A Review of Basic Statistics Principles for Designing Experiments Models for a Single Factor Checking Model Assumptions Transformations of the Response Models with Simple Blocking Structure Extracting Information about Treatments Models with Complex Blocking Structure Replication and Power Dealing with Non-Orthogonality Models for a Single Variate: Simple Linear Regression Checking Model Fit Models for Several Variates: Multiple Linear Regression Models for Variates and Factors Incorporating Structure: Mixed Models Models for Curved Relationships Models for Non-Normal Responses: Generalized Linear Models Practical Design and Data Analysis for Real Studies References Appendices