# Handbook of Regression Modeling in People Analytics

*With Examples in R, Python and Julia*

# Welcome

Welcome to the website for the book *Handbook of Regression Modeling in People Analytics* by Keith McNulty.

**Note**: This book is to be published by Chapman & Hall/CRC later in 2021. The online version of this book is free to read here (thanks to Chapman & Hall/CRC), and licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. If you have any feedback, please feel free to file an issue on GitHub. Thank you!

This book is available in bootstrap format and, for those who prefer, in a more plain gitbook format.

### Notes on data used in this book

For R, Python and Julia users, each of the data sets used in this book can be downloaded individually by following the code in each chapter. Alternatively, packages containing all the data sets used in this book are now available in R and Python. For R users, install and load the `peopleanalyticsdata`

R package.

```
# install peopleanalyticsdata package
install.packages("peopleanalyticsdata")
library(peopleanalyticsdata)
# see a list of data sets
data(package = "peopleanalyticsdata")
# find out more about a specific data set ('managers' example)
help(managers)
```

For Python users , use `pip install peopleanalyticsdata`

to install the package into your environment. Then, to use the package:

```
# import peopleanalyticsdata package
import peopleanalyticsdata as pad
import pandas as pd
# see a list of data sets
pad.list_sets()
# load data into a dataframe
= pad.managers()
df
# find out more about a specific data set ('managers' example)
pad.managers().info()
```

### Solutions to exercises

It is not my intention to publish a comprehensive set of solutions to the exercises in this book. Many of the exercises can be approached in different ways and I think it is important that readers apply their learning without being constrained to an example solution. However, some specific questions have generated considerable interest from readers and I have started to post example solutions to those questions here. Illustrative solutions submitted by readers will progressively be posted there also.

Happy modeling!

*Last update: 07 June 2021*