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Regression for categorical data /

Tutz, Gerhard.

Regression for categorical data /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Regression for categorical data /Gerhard Tutz.
Author:	Tutz, Gerhard.
Published:	Cambridge ;Cambridge University Press,2012.
Description:	x, 561 p. :ill. ;26 cm.
Subject:	Categories (Mathematics)
ISBN:	9781107009653 (hbk.) :

Regression for categorical data /
Tutz, Gerhard.

Regression for categorical data /Gerhard Tutz. - Cambridge ;Cambridge University Press,2012. - x, 561 p. :ill. ;26 cm. - Cambridge series in statistical and probabilistic mathematics.

Includes bibliographical references and indexes.

"Categorical data play an important role in many statistical analyses. They appear whenever the outcomes of one or more categorical variables are observed. A categorical variable can be seen as a variable for which the possible values form a set of categories, which can be finite or, in the case of count data, infinite. These categories can be records of answers (yes/no) in a questionnaire, diagnoses like normal/abnormal resulting from a medical examination or choices of brands in consumer behaviour. Data of this type are common in all sciences that use quantitative research tools, for example social sciences, economics, biology, genetics and medicine, but also engineering and agriculture. In some applications all of the observed variables are categorical and the resulting data can be summarized in contingency tables which contain the counts for combinations of possible outcomes. In other applications categorical data are collected together with continuous variables and one wants to investigate the dependence of one or more categorical variables on continuous and/or categorical variables"--

ISBN: 9781107009653 (hbk.) :NT$2593

LCCN: 2011000390Subjects--Topical Terms:

206297
Categories (Mathematics)

LC Class. No.: QA278.2 / .T88 2012

Dewey Class. No.: 519.5/36

Regression for categorical data /
LDR:01769cam a2200205 a 4500 001 458582
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008 151012s2012 enka b 001 0 eng
010 $a 2011000390
020 $a 9781107009653 (hbk.) : $c NT$2593
035 $a 16605085
040 $a DLC $c DLC $d DLC
042 $a pcc
050 0 0 $a QA278.2 $b .T88 2012
082 0 0 $a 519.5/36 $2 22
100 1 $a Tutz, Gerhard. $3 186308
245 1 0 $a Regression for categorical data / $c Gerhard Tutz.
260 $a Cambridge ; $a New York : $b Cambridge University Press, $c 2012.
300 $a x, 561 p. : $b ill. ; $c 26 cm.
490 0 $a Cambridge series in statistical and probabilistic mathematics
504 $a Includes bibliographical references and indexes.
520 $a "Categorical data play an important role in many statistical analyses. They appear whenever the outcomes of one or more categorical variables are observed. A categorical variable can be seen as a variable for which the possible values form a set of categories, which can be finite or, in the case of count data, infinite. These categories can be records of answers (yes/no) in a questionnaire, diagnoses like normal/abnormal resulting from a medical examination or choices of brands in consumer behaviour. Data of this type are common in all sciences that use quantitative research tools, for example social sciences, economics, biology, genetics and medicine, but also engineering and agriculture. In some applications all of the observed variables are categorical and the resulting data can be summarized in contingency tables which contain the counts for combinations of possible outcomes. In other applications categorical data are collected together with continuous variables and one wants to investigate the dependence of one or more categorical variables on continuous and/or categorical variables"-- $c Provided by publisher.
650 0 $a Categories (Mathematics) $3 206297
650 0 $a Regression analysis. $3 181872