|Exploratory Data Analysis with MATLAB, 2nd Edition|
One of the goals of our first book, Computational Statistics Handbook with MATLAB, was to show some of the key concepts and methods of computational statistics and how they can be implemented in MATLAB. A core component of computational statistics is the discipline known as exploratory data analysis or EDA. Thus, we see this book as a complement to the first one with similar goals: to make exploratory data analysis techniques available to a wide range of users.
This text is not focused on the theoretical aspects of the methods. Rather, the main focus of this book is on the use of the EDA methods. Thus, we do not dwell so much on implementation and algorithmic details. Instead, we show students and practitioners how the methods can be used for exploratory data analysis by providing examples and applications.
Topics covered include: linear and nonlinear dimensionality reduction, data tours, finding clusters, model-based clustering, smoothing, visualizing clusters, exploring distribution shapes, and multivariate visualization.
Click here to order the book from Amazon.
Click here to download the Exploratory Data Anallysis Toolbox for MATLAB. This links to the MATLAB code for the examples found in the book. Because EDA involves a lot of colorful visualizations, we provide color versions of most figures in the book.
The data sets are available in chunks. Most of the data sets are in this file. Here are links to some other data sets:
|Last updated: December 2010|