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Handbook of regression modeling in people analytics = with examples in R and Python /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Handbook of regression modeling in people analytics/ Keith McNulty.
Reminder of title:	with examples in R and Python /
Author:	McNulty, Keith.
Published:	Boca Raton, FL :CRC Press, : 2021.,
Description:	1 online resource.
[NT 15003449]:	The importance of regression in people analytics -- The basics of the R Programming Language -- Statistics foundations -- Linear regression for continuous outcomes -- Binomial logistic regression for binary outcomes -- Multinomial logistic regression for nominal category outcomes -- Proportional odds logistic regression for ordered category outcomes -- Modeling explicit and latent hierarchy in data -- Survival analysis for modeling singular events over time -- Alternative technical approaches in R and Python -- Power analysis to estimate required sample sizes for modeling -- Further exercises for practice.
Subject:	Regression analysis. -
Online resource:	https://www.taylorfrancis.com/books/9781003194156
ISBN:	9781003194156

Handbook of regression modeling in people analytics = with examples in R and Python /
McNulty, Keith.

Handbook of regression modeling in people analyticswith examples in R and Python /[electronic resource] :Keith McNulty. - 1st ed. - Boca Raton, FL :CRC Press,2021. - 1 online resource.

Includes bibliographical references and index.

The importance of regression in people analytics -- The basics of the R Programming Language -- Statistics foundations -- Linear regression for continuous outcomes -- Binomial logistic regression for binary outcomes -- Multinomial logistic regression for nominal category outcomes -- Proportional odds logistic regression for ordered category outcomes -- Modeling explicit and latent hierarchy in data -- Survival analysis for modeling singular events over time -- Alternative technical approaches in R and Python -- Power analysis to estimate required sample sizes for modeling -- Further exercises for practice.

"This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling. Although it is primarily focused on examples related to the analysis of people and talent, the methods easily transfer to any discipline. The book hits a 'sweet spot' where there is just enough mathematical theory to support a strong understanding of the methods, but with a step-by-step guide and easily reproducible examples and code, so that the methods can be put into practice immediately. This makes the book accessible to a wide readership, from public and private sector analysts and practitioners to students and researchers"--

ISBN: 9781003194156

LCCN: 2021017167Subjects--Topical Terms:

529831
Regression analysis.

LC Class. No.: QA278.2

Dewey Class. No.: 519.5/36

Handbook of regression modeling in people analytics = with examples in R and Python /
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020 $z 9781032041742 $q (hardback)
020 $z 9781032046631 $q (paperback)
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040 $a DLC $b eng $c DLC $d DLC
041 0 $a eng
050 0 0 $a QA278.2
082 0 0 $a 519.5/36 $2 23
100 1 $a McNulty, Keith. $3 3720422
245 1 0 $a Handbook of regression modeling in people analytics $h [electronic resource] : $b with examples in R and Python / $c Keith McNulty.
250 $a 1st ed.
260 $a Boca Raton, FL : $b CRC Press, $c 2021.
300 $a 1 online resource.
504 $a Includes bibliographical references and index.
505 0 $a The importance of regression in people analytics -- The basics of the R Programming Language -- Statistics foundations -- Linear regression for continuous outcomes -- Binomial logistic regression for binary outcomes -- Multinomial logistic regression for nominal category outcomes -- Proportional odds logistic regression for ordered category outcomes -- Modeling explicit and latent hierarchy in data -- Survival analysis for modeling singular events over time -- Alternative technical approaches in R and Python -- Power analysis to estimate required sample sizes for modeling -- Further exercises for practice.
520 $a "This book is a learning resource on inferential statistics and regression analysis. It teaches how to do a wide range of statistical analyses in both R and in Python, ranging from simple hypothesis testing to advanced multivariate modelling. Although it is primarily focused on examples related to the analysis of people and talent, the methods easily transfer to any discipline. The book hits a 'sweet spot' where there is just enough mathematical theory to support a strong understanding of the methods, but with a step-by-step guide and easily reproducible examples and code, so that the methods can be put into practice immediately. This makes the book accessible to a wide readership, from public and private sector analysts and practitioners to students and researchers"-- $c Provided by publisher.
588 $a Description based on print version record and CIP data provided by publisher; resource not viewed.
650 0 $a Regression analysis. $3 529831
650 0 $a Mathematical statistics. $3 516858
650 0 $a R (Computer program language) $3 784593
650 0 $a Python (Computer program language) $3 729789
856 4 0 $u https://www.taylorfrancis.com/books/9781003194156