MBAD6224.10P – Decision Making and Data Analysis Fall 2023

General Instructions

Please read carefully: You are to work strictly individually on this assignment. You must not receive or give any help in working on this assignment, and you must not discuss or exchange any information (electronic or other) with anyone about  it.  Having your work  automatically  backed  up to  a  drive accessible to others is a violation of this rule. Read the assignment entirely, including the instructions at the end, before starting to work. Provide explanations for your answers to the questions.

Due date:  The assignment is due on Sunday 24 September, 11:59pm EST.

What to turn in:  Submit a single Excel file containing all your work, as detailed in Instructions at the end. When finished, write the following statement at the top of the first worksheet: “I, your full name, attest that I did not receive or provide any help in working on this assignment.”

How to turn in your work:  Submit your work on Blackboard by clicking on “Submit Assignment” in the left pane menu. If you submit your work multiple times, only your last submission will be considered.

Medical Care Costs

A health insurance company would like to predict the medical care costs that it will have to pay, based on characteristics of the health policy beneficiary. Data on the following variables were gathered:

-     Gender: gender of primary beneficiary; 1 = Female, 0 = Male

-     Age: age of primary beneficiary

-     BMI: Body Mass Indexof primary beneficiary. Calculated from a person's weight and height, BMI is an approximate measure of total body fat

-     Smoker: binary variable indicating whether the primary beneficiary is a smoker; 1 = Smoker, 0 = Non-smoker

-     Dependents: number of dependents (e.g., children) covered under the health insurance policy

-     Charges: medical care costs (in USD) billed to health insurance over a calendar year

The data on the above variables for a sample of 1338 policy holders is in the worksheet named ‘Sheet1’ in the accompanying Excel file.

a)    Using the data  in Sheet1, build a linear regression model to relate Charges, as the dependent variable, to the other variables. Show the regression output only for the model you choose to retain, and explain the steps you took to arrive at your model. Write down the regression equation resulting from your model.

Sheet2 of the data file includes an additional variable called ‘Smoker x BMI’. This new variable is the product  of  the  variables  ‘Smoker’  and  ‘BMI’.  Such  a  product  variable  can  capture  the  possible interaction of two variables, for example, the fact that the combination of being a smoker and having a high BMI may have an important effect beyond either factor by itself.