**FOUNDATIONS**

Philosophical and Historical Foundations

Introduction

Nature of Science

Scientific Principles

Scientific Method

Scientific Hypotheses

Logic

Variability and Uncertainty in Investigations

Science and Statistics

Statistics and Biology

**Introduction to Probability**

Introduction: Models for Random Variables

Classical Probability

Conditional Probability

Odds

Combinatorial Analysis

Bayes Rule

**Probability Density Functions**

Introduction

Introductory Examples of pdfs

Other Important Distributions

Which pdf to Use?

Reference Tables

**Parameters and Statistics**

Introduction

Parameters

Statistics

OLS and ML Estimators

Linear Transformations

Bayesian Applications

**Interval Estimation: Sampling Distributions, Resampling Distributions, and Simulation Distributions**

Introduction

Sampling Distributions

Confidence Intervals

Resampling Distributions

Bayesian Applications: Simulation Distributions

**Hypothesis Testing**

Introduction

Parametric Frequentist Null Hypothesis Testing

Type I and Type II Errors

Power

Criticisms of Frequentist Null Hypothesis Testing

Alternatives to Parametric Null Hypothesis Testing

Alternatives to Null Hypothesis Testing

**Sampling Design and Experimental Design**

Introduction

Some Terminology

The Question Is: What Is the Question?

Two Important Tenets: Randomization and Replication

Sampling Design

Experimental Design

**APPLICATIONS**

Correlation

Introduction

Pearson’s Correlation

Robust Correlation

Comparisons of Correlation Procedures

**Regression**

Introduction

Linear Regression Model

General Linear Models

Simple Linear Regression

Multiple Regression

Fitted and Predicted Values

Confidence and Prediction Intervals

Coefficient of Determination and Important Variants

Power, Sample Size, and Effect Size

Assumptions and Diagnostics for Linear Regression

Transformation in the Context of Linear Models

Fixing the *Y*-Intercept

Weighted Least Squares

Polynomial Regression

Comparing Model Slopes

Likelihood and General Linear Models

Model Selection

Robust Regression

Model II Regression (*X *Not Fixed)

Generalized Linear Models

Nonlinear Models

Smoother Approaches to Association and Regression

Bayesian Approaches to Regression

**ANOVA**

Introduction

One-Way ANOVA

Inferences for Factor Levels

ANOVA as a General Linear Model

Random Effects

Power, Sample Size, and Effect Size

ANOVA Diagnostics and Assumptions

Two-Way Factorial Design

Randomized Block Design

Nested Design

Split-Plot Design

Repeated Measures Design

ANCOVA

Unbalanced Designs

Robust ANOVA

Bayesian Approaches to ANOVA

**Tabular Analyses**

Introduction

Probability Distributions for Tabular Analyses

One-Way Formats

Confidence Intervals for p

Contingency Tables

Two-Way Tables

Ordinal Variables

Power, Sample Size, and Effect Size

Three-Way Tables

Generalized Linear Models

**Appendix**

**References**

**Index**