Handbook of Regression Modeling in People Analytics:With Examples in R and Python

Handbook of Regression Modeling in People Analytics:With Examples in R and Python

by: Keith McNulty (Author)

Publisher: Chapman and Hall/CRC

Edition: 1st

Publication Date: 2021/7/30

Language: English

Print Length: 272 pages

ISBN-10: 1032041749

ISBN-13: 9781032041742

Book Description

Despite the recent rapid growth in machine leaing 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 leaing 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.

About the Author

Despite the recent rapid growth in machine leaing 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 leaing 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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