As you read in Data Problem #$1,$ Ms$.$ Burke had a meeting with PLE$$s human resources director to discuss how they might increase the retention rate for its field service staff. Your analysis was helpful, but it caused everyone to think not only about the costs of turnover and how it can be reduced, but also about the negative impact of absenteeism$.$ The company runs with minimal $$backup people$$ to fill in when someone is out due to sickness or otherwise. Thus, absenteeism causes more immediate problems compared to turnover. Additional data were added to the database that you worked with on Data Problem $1$ to allow you to look for additional variables that the company can use as predictors of absenteeism$.$ The idea is that if there are variables that are related to absenteeism$,$ they could be measured at the time of hire and used in the employee selection process. The spreadsheet Data Problem $2$ is provided to you in order to make recommendations on which $($if any$)$ of the variables can be used as screening devices at the time of hire. There is now data for $104$ employees $($attached$)$ which includes data from the time of hire along with data from the time they have worked at PLE. HR has included a measure of job performance so you should be able to make some strong recommendations about the variables that are related to absenteeism$.$ Please submit your findings with your recommendations in a concise report. Cover everything, but do not go over $5$ pages if possible.