There are various factors that affect an individual’s decision to leave a job. Whether the organization is large or small the main issue or challenge faced by the HR is Predicting attrition. In today’s contemporary scenario, when an individual leaves the job, it causes a lot of disturbances in the organization. If it is a small organization the disturbance is even greater. Hence it is important to understand and manage attrition.

For large companies it becomes very difficult to analyse every cases, one by one, to understand the cause of attrition.  But what if we can predict attrition? Statisical Analysis has given us the power to predict the probability of an employee leaving the company by virtue of fitting a well selected and accurate model. This can be an enormously useful information for the HRs' which will allow them to figure out which employee is more likely to leave the company and decide upon the fact if that employee can be retained or they should look for replacement. It is also a fact that more the number of years spend by a person in a company more his/her chance of leaving the company. Advanced Statistical techniques allows us to quantify the chance of an employee leaving the company given that he has already worked for a certain number of years in the company.

We have two objectives in this projects:

1. To predict the probability of an employee leaving a company given the information of the employee using logistic regression, and

2. To estimate the Kaplan-Mayer's survival probability of an employer surviving in the company given than he/she had survived past a specified number of years.