A financial institution has a large dataset of information provided by its customers when they apply for a credit card. This customer information includes the following variables:

• Annual household income (in thousands of dollars)

• Household size (number of people)

• Number of years of post-high school education

• Number of hours per week watching television

• Age

• Gender

  In addition, the financial institution has records of the credit card charges accrued by each customer over the past year.

  The data for this question is provided in the worksheet named Part 4.

• a. [5 marks] Plot histograms to contrast the distribution of annual credit card charges for 1) People with zero years of post-high school education vs. People with at least 1 year of post-high school education, and 2) Female vs. Male. Describe the overall shape of each histogram and comment on any observable differences.

• b. [10 marks] Estimate a multiple linear regression model in which the dependent variable is the credit card charges accrued by each customer in the data over the past year, and the independent variables are all the variables the financial institution collected when the customer first applied for a credit card (e.g. annual household income). What is the estimated regression model (equation)? Hint: For Gender, create a dummy variable that takes 1 if the customer is female and 0 if male.

c. [15 marks] Interpret each of the regression coefficients and comment on both their economic and statistical significance. For each significant regressor (at a 5% significance level) provide a potential explanation for its statistical relationship with the dependent variable.