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Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data – eBook

eBook details

  • Authors: Michael Friendly, David Meyer
  • File Size: 7 MB
  • Format: PDF
  • Length: 562 pages
  • Publisher: Chapman and Hall/CRC
  • Publication Date: December 16, 2015
  • Language: English
  • ASIN: B019FNKP1Q
  • ISBN-10: 149872583X
  • ISBN-13: 9781498725835

Original price was: $70.97.Current price is: $17.00.

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Author(s)

David Meyer

Michael Friendly

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 (PDF) presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It describes how to use graphical methods for exploring data, locating unusual features, visualizing fitted models, and presenting results.

The ebook is designed for advanced undergraduate and graduate students in the social and health sciences, epidemiology, economics, statistics, business, and biostatistics, together with researchers, methodologists, and consultants who can use the methods with their own data and analyses. Along with describing the necessary statistical theory, the authors demonstrate the practical application of the techniques to a large number of substantive problems, including how to organize data, conduct an analysis, create informative graphs, and analyze what the charts reveal about the data.

The first part of the ebook includes introductory material on graphical methods for discrete data, basic R skills, and plans for fitting and visualizing one-way discrete distributions. The second part emphasises on simple, traditional nonparametric tests and exploratory methods for visualizing patterns of association in two-way and larger frequency tables. The last section of the textbook discusses model-based methods for the analysis of discrete data.

NOTE: The product includes the ebook, Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data in PDF. Access codes are not included.

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