By Alan Agresti

Praise for the second one Edition

"A must-have ebook for someone looking forward to to do learn and/or purposes in express info analysis."
Statistics in Medicine

"It is a complete pride studying this book."
Pharmaceutical Research

"If you do any research of specific facts, this can be a vital machine reference."
Technometrics

The use of statistical equipment for reading specific information has elevated dramatically, relatively within the biomedical, social sciences, and monetary industries. Responding to new advancements, this e-book bargains a finished therapy of an important equipment for express information analysis.

Categorical facts research, 3rd Edition summarizes the newest tools for univariate and correlated multivariate specific responses. Readers will discover a unified generalized linear types strategy that connects logistic regression and Poisson and damaging binomial loglinear types for discrete info with common regression for non-stop info. This version additionally features:

  • An emphasis on logistic and probit regression equipment for binary, ordinal, and nominal responses for self sustaining observations and for clustered info with marginal versions and random results models
  • Two new chapters on replacement equipment for binary reaction info, together with smoothing and regularization equipment, type equipment akin to linear discriminant research and type bushes, and cluster analysis
  • New sections introducing the Bayesian strategy for ways in that chapter
  • More than a hundred analyses of information units and over six hundred exercises
  • Notes on the finish of every bankruptcy that offer references to fresh examine and subject matters now not lined within the textual content, associated with a bibliography of greater than 1,200 sources
  • A supplementary site displaying how you can use R and SAS; for all examples within the textual content, with details additionally approximately SPSS and Stata and with workout solutions

Categorical info research, 3rd Edition is a useful device for statisticians and methodologists, reminiscent of biostatisticians and researchers within the social and behavioral sciences, medication and public well-being, advertising, schooling, finance, organic and agricultural sciences, and business caliber control.

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