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Handbook Of Regression Modeling In People Analytics With Examples In R And Python at Meripustak

Handbook Of Regression Modeling In People Analytics With Examples In R And Python by Keith Mcnulty, T&F/Crc Press

Books from same Author: Keith Mcnulty

Books from same Publisher: T&F/Crc Press

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  • General Information  
    Author(s)Keith Mcnulty
    PublisherT&F/Crc Press
    Edition1st Edition
    ISBN9781032041742
    Pages272
    BindingHardcover
    LanguageEnglish
    Publish YearJanuary 2022

    Description

    T&F/Crc Press Handbook Of Regression Modeling In People Analytics With Examples In R And Python by Keith Mcnulty

    Despite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening. Regression analysis is the best ‘swiss army knife’ we have for answering these kinds of questions.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.Key Features:16 accompanying datasets across a wide range of contexts (e.g. academic, corporate, sports, marketing)Clear step-by-step instructions on executing the analysesClear guidance on how to interpret resultsPrimary instruction in R but added sections for Python codersDiscussion exercises and data exercises for each of the main chaptersFinal chapter of practice material and datasets ideal for class homework or project work.



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