Reference - Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data (Chapman & Hall/CRC Texts in Statistical Science)

Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data (Chapman & Hall/CRC Texts in Statistical Science)

Name: Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data (Chapman & Hall/CRC Texts in Statistical Science)
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3.8 of 5 Stars: Reference - Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data (Chapman & Hall/CRC Texts in Statistical Science)

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Book Synopsis: An Applied Treatment of Modern Graphical Methods for Analyzing Categorical Data
Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It explains how to use graphical methods for exploring data, spotting unusual features, visualizing fitted models, and presenting results.
The book is designed for advanced undergraduate and graduate students in the social and health sciences, epidemiology, economics, business, statistics, and biostatistics as well as researchers, methodologists, and consultants who can use the methods with their own data and analyses. Along with describing the necessary statistical theory, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to organize data, conduct an analysis, produce informative graphs, and evaluate what the graphs reveal about the data.
The first part of the book contains introductory material on graphical methods for discrete data, basic R skills, and methods for fitting and visualizing one-way discrete distributions. The second part focuses on simple, traditional nonparametric tests and exploratory methods for visualizing patterns of association in two-way and larger frequency tables. The final part of the text discusses model-based methods for the analysis of discrete data.
Web Resource
The data sets and R software used, including the authors' own vcd and vcdExtra packages, are available at http://cran.r-project.org.

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Looking for a comprehensive guide on analyzing categorical and count data? Look no further! Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data is your ultimate resource. Whether you're an advanced undergraduate student, graduate student, researcher, or consultant, this book provides the applied treatment of modern methods for analyzing categorical data that you need.

Why should you choose this book? Not only does it offer a thorough explanation of how to use graphical methods for exploring data and presenting results, but it also provides practical examples and real-life applications. You'll learn how to organize data, conduct an analysis, and produce informative graphs that reveal valuable insights about your data.

What sets this book apart is its emphasis on practicality. The authors not only describe the necessary statistical theory but also illustrate how to apply the techniques to a wide range of substantive problems. Whether you're in the social and health sciences, economics, business, or biostatistics, you'll find this book invaluable.

But that's not all! Discrete Data Analysis with R also provides web resources to enhance your learning experience. You'll have access to the authors' own vcd and vcdExtra packages, as well as data sets and R software, making it easier for you to apply the methods to your own data and analyses.

Don't miss out on this essential tool for analyzing categorical and count data. Take your data analysis skills to the next level with Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data. Get your copy today!

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