Welcome to HR Analytics.live
1 Introduction
2 Getting Started with Data in R
I Data Science with tidyverse
3 Data Visualization
4 Data Wrangling
5 Data Importing and “Tidy” Data
II Data Modeling with moderndive
6 Basic Regression
7 Multiple Regression
III Statistical Inference with infer
8 Sampling
9 Bootstrapping and Confidence Intervals
10 Hypothesis Testing
11 Inference for Regression
IV Conclusion
12 Tell Your Story with Data
V HR Analytics practical examples
13 Gender Pay Gap
14 Stop appraisals
15 HR Service Desk
16 Personality insights
17 Commuting time
18 Organisational network analysis
19 Job classification analysis
- 19.0.1 Final evaluation of the various models
20 Masking HR data
- 20.0.1 Whitehouse dataset
- 20.0.2 Fertility dataset
21 Absenteeism in manufacturing
- 21.0.1 For expediency we will delete the problem records in the dataset.
22 Absenteeism at work
23 Accidents at work
24 Attrition
25 Interview attendance problem
26 Ranking Medical Schools
27 Webscraping LinkedIn
28 HR dashboards
29 HR Analytics product with Shiny
Appendix
A Statistical Background
B Inference Examples
C Tips and Tricks
D Learning Check Solutions
E Versions of R Packages Used
F Archive HR datasets
References

HR Analytics in R

Chapter 24 Attrition

Here we introduce attrition.