CRC Press A Course in Categorical Data Analysis: 45 (Chapman & Hall/CRC Texts in Statistical Science)

Categorical data-comprising counts of individuals, objects, or entities in different categories-emerge frequently from many areas of study, including medicine, sociology, geology, and education. They provide important statistical information that can lead to real-life conclusions and the discovery of fresh knowledge. Therefore, the ability to manipulate, understand, and interpret categorical data becomes of interest-if not essential-to professionals and students in a broad range of disciplines. Although t-tests, linear regression, and analysis of variance are useful, valid methods for analysis of measurement data, categorical data requires a different methodology and techniques typically not encountered in introductory statistics courses. Developed from long experience in teaching categorical analysis to a multidisciplinary mix of undergraduate and graduate students, A Course in Categorical Data Analysis presents the easiest, most straightforward ways of extracting real-life conclusions from contingency tables. The author uses a Fisherian approach to categorical data analysis and incorporates numerous examples and real data sets. Although he offers S-PLUS routines through the Internet, readers do not need full knowledge of a statistical software package. In this unique text, the author chooses methods and an approach that nurtures intuitive thinking. He trains his readers to focus not on finding a model that fits the data, but on using different models that may lead to meaningful conclusions. The book offers some simple, innovative techniques not highighted in other texts that help make the book accessible to a broad, interdisciplinary audience. A Course in Categorical Data Analysis enables readers to quickly use its offering of tools for drawing scientific, medical, or real-life conclusions from categorical data sets. Review "presents an interesting and alternative view of categorical data analysis (CDA)This book would be appropriate for upper undergraduates or master's level courses in statistics for non-majors who need an overview of CDA without going into great detail and theoryrepresents a fresh perspective on CDA. It is well worth a look, both by practitioners who use these methods in their research and by instructors who plan to teach courses on this subject The author has extensive teaching experience at the University of Wisconsin-Madison and at the University of Edinburgh, and the choice of topics in this book reflects that experience Each chapter is followed by useful exercises that should aid in developing an understanding of the presented material Its many biological and medical examples, some developed in detail, make it especially useful for students with interests in the health sciences." --C. B. Borkowf, National Cancer Institute, Bethesda, MD, in Biometrics, December 2000 "This book offers something differentwhat a wealth of detail and insight he develops! Copious numerical examples are discussed alongside the theory, and each of these are interpreted in the context of the study that generated the dataa welcome addition to the literature." --J. M. Juritz, Short Book Reviews of the ISI, April 2000 "a unique work in the implementation of techniques and methodologies neededare not usually found in introductory statistics coursesHighly recommended for upper-division undergraduates and graduate students, faculty, and professionals." --D. J. Gougeon, University of Scranton in CHOICE "This book would be appropriate for upper undergraduate or master's level courses in statistics for non-majors whoneed an overview of CDA without going into great detail and theory. Its many biological and medical examples, some developed in detail, make it especially useful for students with interests in the health sciences." C.B. Borkowf, National Cancer Institute, Bethesda, maryland, USA "the excellent discussion of Simpson's paradox, could be included in more general survey courses." C.B. Borkowf, Nationa