Statistical analysis of employee retention

Baoyi Peng

doi:10.1117/12.2628107

22 April 2022 Statistical analysis of employee retention

Baoyi Peng

Proceedings Volume 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021); 1216303 (2022) https://doi.org/10.1117/12.2628107
Event: International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 2021, Nanjing, China

Abstract

Employees are essential to the company, and suitable employees will greatly promote the company's development. Turnover of employees will bring huge economic and time losses to the company. In order to avoid such loss, this paper establishes a logistic regression model to analyze the important reasons for employee dismissal. We use the IBM employee attrition dataset, to import the data into RStudio; delete the null values and other unnecessary values in the dataset, transform the categorical columns into numerical columns; do the feature selection using a logistic regression algorithm, then build the model and use the ROC curve to get the accuracy of the test. We find that many reasons influence employees to leave the company, but the most important five are marital status, business travel, age, years at the company, and the number of companies. Companies can reduce employee attrition rates by selecting older, married employees who have worked for fewer companies. For employees already on the job, the frequency of business travel should be reduced. The longer employees stay, the less likely they leave.

Citation Download Citation

Baoyi Peng "Statistical analysis of employee retention", Proc. SPIE 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 1216303 (22 April 2022); https://doi.org/10.1117/12.2628107

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