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

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.

List of contents

1. The Importance of Regression in People Analytics. 2. The Basics of the R Programming Language. 3. Statistics Foundations. 4. Linear Regression for Continuous Outcomes. 5. Binomial Logistic Regression for Binary Outcomes. 6. Multinomial Logistic Regression for Nominal Category Outcomes. 7. Ordinal Logistic Regression for Ordered Category Outcomes. 8. Modeling Explicit and Latent Hierarchical Structure in Data. 9. Survival Analysis for Modeling the Occurrence of Singular Events Over Time. 10. Alternative Technical Approaches in R and Python. 11. Power Analysis to Estimate Required Sample Sizes for Inferential Modeling. 12. Further Exercises for Practice.

About the author

Keith McNulty, PhD is a leading practitioner of applied statistics, psychometrics and people analytics. He is currently Global Director of Talent Science and Analytics at McKinsey and Company.

Summary

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.

Product details

• Authors: Keith McNulty
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 31.08.2021
• EAN: 9781032041742
• ISBN: 978-1-0-3204174-2
• No. of pages: 272
• Subjects: Humanities, art, music > Psychology > Basic principles; Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Non-fiction book > Psychology, esoterics, spirituality, anthroposophy > Psychology: general, reference works; MATHEMATICS / Probability & Statistics / General, PSYCHOLOGY / Research & Methodology, Psychological methodology, Probability & statistics, Probability and statistics, Regression Modeling