1.

Exploratory Data Analysis

This chapter presents the assumptions, principles, and techniques necessary to gain insight into data via EDA--exploratory data analysis.

1. EDA Introduction

1. What is EDA?
   
2. EDA vs Classical & Bayesian
   
3. EDA vs Summary
   
4. EDA Goals
   
5. The Role of Graphics
   
6. An EDA/Graphics Example
   
7. General Problem Categories
   

2. EDA Assumptions

1. Underlying Assumptions
2. Importance
3. Techniques for Testing Assumptions
4. Interpretation of 4-Plot
5. Consequences

3. EDA Techniques

1. Introduction
2. Analysis Questions
3. Graphical Techniques: Alphabetical
4. Graphical Techniques: By Problem Category
5. Quantitative Techniques
6. Probability Distributions

4. EDA Case Studies

1. Introduction
2. By Problem Category

Detailed Chapter Table of Contents
References
Dataplot Commands for EDA Techniques