1. Assessing how lifestyle could affect sick days.

1.1.

A company HR department launched a project to study how the number of reported sick days in a year is affected by the employees’ demographics and lifestyle and to build a model to predict annual sick days of current and potential employees. A survey was carried out on the demographics and lifestyles for a sample of 10 employees, and the survey results were recorded in an Excel workbook, ASSN2data.xlsx.

1.2.

The data collected consist of:

• Number of sick days recorded in a year
• Age of employee, recorded in years
• Weight of employee, recorded in kilogrammes (kg)
• Height of employee, recorded in metres (m)
• Number of hours of sleep per day (for 7 consecutive days)
• Number of hours of exercises per day (for 7 consecutive days)
• Number of calories consumed per day (for 7 consecutive days)
• Number of alcoholic drinks over 7 days
• Number of cigarettes smoked over 7 days

1.3.

Based on the data in the Excel workbook, build a model to predict number of sick days reported based on the employees’ demographics and lifestyle. Describe how each type of demographic data and lifestyle data affect the number of sick days reported. You may want to use correlational study and multiple linear regression to do your analysis and build the predictive model.

1.4.

Based on your analysis, propose a regression model to use selected demographics and lifestyle habits to predict sick days taken per year by an employee.

1.5.

Submit your report as a Word file, together with your Excel workbook containing your analysis. Your submission filenames must contain your admin no.

Healthcare Analytics Page 2 of 2 Effective Date: 21 Apr 2025
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