Table of Contents

Front Matter.
Introduction to R.
Data Sets.
Introductory Statistical Principles.
Sampling and Experimental Design with R.
Graphical Data Presentation.
Simple Hypothesis Testing-One and Two Population Tests.
Introduction to Linear Models.
Correlation and Simple Linear Regression.
Multiple and Curvilinear Regression.
Single Factor Classification (ANOVA).
Nested ANOVA.
Factorial ANOVA.
Unreplicated Factorial Designs-Randomized Block and Simple Repeated Measures.
Partly Nested Designs: Split Plot and Complex Repeated Measures.
Analysis of Covariance (ANCOVA).
Simple Frequency Analysis.
Generalized Linear Models (GLM).
R Index.
Statistics Index.