ABSTRACT

Exploratory data analysis (EDA) was conceived at a time when computers were not widely used, and thus computational ability was rather limited. As computational sophistication has increased, EDA has become an even more powerful process for visualizing and summarizing data before making model assumptions to generate hypotheses, encompassing larger a

part |2 pages

Part I: Introduction to Exploratory Data Analysis

chapter 1|26 pages

Introduction to Exploratory Data Analysis

part |2 pages

Part II: EDA as Pattern Discovery

chapter 2|30 pages

Dimensionality Reduction - Linear Methods

chapter 4|24 pages

Data Tours

chapter 5|44 pages

Finding Clusters

chapter 6|34 pages

Model-Based Clustering

chapter 7|34 pages

Smoothing Scatterplots

part |2 pages

Part III: Graphical Methods for EDA

chapter 8|26 pages

Visualizing Clusters

chapter 9|34 pages

Distribution Shapes

chapter 10|44 pages

Multivariate Visualization