squared coefficients residual plots forecasting B u s i n e s s F i n a n c e

To run, analyze, and replicate regressions.

Instructions

1. Regression Analysis

Quantity Price Income Analysis (10 pts.)

Run a regression on the Quantity Price Income.xls dataset. 

The dependent variable is Quantity and the independent variables are Price & Income.

Using the regression lecture as a template, write a Word document reporting your results. Be sure to include the values for the topics listed below:

• Significance & P-values
• R-Squared
• Coefficients

Residual Plots

1. 2. Season Ticket Sales Analysis Report (10 pts.)    a. Run a regression on the SeasonTicketSales.xls dataset. This dataset gives football team’s season-ticket sales, percentage of games won, and number of active alumni for the years from 1998 to 2011. The dependent variable is SeasonTicketSales and the independent variables are Percentage of Games Won & Number of Active Alumni.B. Using the regression lecture as a template, write a Word document reporting your results. Be sure to include the values for the topics listed below:
2. Significance & P-values
3. R-Squared
4. Coefficients

Residual Plots

3. HBAT sample dataset (20 pts)

Run a regression on the HBATSample.xls dataset. 

The dependent variable is CustomerSatisfaction and the independent variables are ProductQuality and Ecommerce Activities.

Using the regression lecture as a template, write a Word document reporting your results. Be sure to include the values for the topics listed below:

1. Significance & P-values
2. R-Squared
3. Coefficients
4. Residual Plots
5. Forecasting the change in ProductQuality and ECommerceActivities on Customer Satisfaction.

ProductQuality

Holding all other variables constant, calculate the expected value of CustomerSatisfaction with an increase of the average value of ProductQuality.

1. Holding all other variables constant, calculate the expected value of CustomerSatisfaction with a decrease of one standard deviation to the average value of ProductQuality.
2. ECommerceActivities

Holding all other variables constant, calculate the expected value of CustomerSatisfaction with an increase of one standard deviation to the average value of ECommerceActivities.

1. Holding all other variables constant, calculate the expected value of CustomerSatisfaction with a deacrease of one standard deviation to the average value of ECommerceActivities.