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Discrete Data Analysis with R - Visualization and Modeling Techniques for Categorical and Count Data (Hardcover)
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Discrete Data Analysis with R - Visualization and Modeling Techniques for Categorical and Count Data (Hardcover)
Series: Chapman & Hall/CRC Texts in Statistical Science
Expected to ship within 9 - 15 working days
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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 ResourceThe 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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