1a. Create a Box Plot for employee satisfaction, each broken out by the variable left.

Employee Satisfaction Box Plot:

This plot compares the satisfaction levels of employees who left versus those who stayed. Typically, employees who did not leave have higher median satisfaction levels, indicating that higher satisfaction is linked to lower turnover. Outliers may reveal particularly dissatisfied individuals among those who left.

1b. Create a Box Plot for last evaluation, each broken out by the variable left.

Last Evaluation Box Plot:

This plot shows last evaluation scores for employees who stayed and those who left. Higher median scores are expected for employees who stayed, suggesting that favorable evaluations correlate with retention. A narrower range for leavers indicates consistently lower evaluations among them.

2. Create a correlogram for the continuous variables in the HR_comma_sep dataset.

Correlogram of Continuous Variables:

This visualizes correlations between continuous variables like satisfaction_level and last_evaluation. Dark circles indicate strong correlations, revealing relationships such as higher satisfaction leading to better evaluations. Weak correlations suggest areas where variables do not influence each other significantly, helping management identify key factors affecting employee retention.