Applied logistic regression (Wiley Series in probability and statistics) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Applied logistic regression (Wiley Series in probability and statistics)

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David W. Hosmer 作者
Wiley-Interscience Publication
译者
2000-09-15 出版日期
392 页数
USD 125.00 价格
Hardcover
Wiley Series in Probability and Statistics 丛书系列
9780471356325 图书编码

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Applied logistic regression (Wiley Series in probability and statistics) 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Applied logistic regression (Wiley Series in probability and statistics) 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Applied logistic regression (Wiley Series in probability and statistics) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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Applied logistic regression (Wiley Series in probability and statistics) 在线电子书 图书描述

From the reviews of the First Edition.

"An interesting, useful, and well-written book on logistic regression models . . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references."

—Choice

"Well written, clearly organized, and comprehensive . . . the authors carefully walk the reader through the estimation of interpretation of coefficients from a wide variety of logistic regression models . . . their careful explication of the quantitative re-expression of coefficients from these various models is excellent."

—Contemporary Sociology

"An extremely well-written book that will certainly prove an invaluable acquisition to the practicing statistician who finds other literature on analysis of discrete data hard to follow or heavily theoretical."

—The Statistician

In this revised and updated edition of their popular book, David Hosmer and Stanley Lemeshow continue to provide an amazingly accessible introduction to the logistic regression model while incorporating advances of the last decade, including a variety of software packages for the analysis of data sets. Hosmer and Lemeshow extend the discussion from biostatistics and epidemiology to cutting-edge applications in data mining and machine learning, guiding readers step-by-step through the use of modeling techniques for dichotomous data in diverse fields. Ample new topics and expanded discussions of existing material are accompanied by a wealth of real-world examples-with extensive data sets available over the Internet.

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