Fundamental Concepts in Experiment Design (Statistics)

~ Fundamental Concepts in Experiment Design ~
This book covers several core concepts in the design of experiments and their statistical analysis. Emphasis is placed on the analysis of Gaussian-distributed responses, using ANOVA and Linear Modeling. The first 20 pages introduce the theory of design, and the remaining 280 pages cover several worked examples.

Part 1 - Theory Experiment Overview Design Phase Predictor Mathematical Flavor Fixed vs. Random Effect Crossed vs. Nested Categorical Experiment vs. Grouping Interventional vs. Observational Repeated Measures Object Constructed vs. Pre-Existing Response Mathematical Flavor Statistical Distribution Replicates Linear Model Equation Implementation Phase Randomization Site Randomization Type Hidden Predictors Randomization Rules of Thumb Analysis Phase
Part 2 - Example Experiments Designs with One Experiment Predictor Two-Group Comparison Three-Group Comparison Linear Regression Designs with One Experiment Predictor and One Grouping Predictor Two-Group Comparison + Fixed Effect Blocks Two-Group Comparison + Random Effect Blocks Two-Group Comparison + Object, i.e. a "Repeated Measures" design Linear Regression + Blocks Designs with Two Experiment Predictors Crossed Categorical Predictors Nested Categorical Predictor Designs with Two Experiment Predictors and One Grouping Predictor 2 Crossed Predictors + Blocks Split Plot, Type A 2 Factor Fully "Repeated Measures" 2 Factor Partially "Repeated Measures"