# BUS 6073 AA #5 (Week 5) Assignment

BUS 6073 AA #5 (Week 5)

Description of Case Studies

Case #1: (50 points):

Your client is interested in determining if “Fuel Economy” is influenced by either Temperature and / or Humidity. In this study, the dependent variable (DV) is “Fuel Economy” and is labeled, MPG (miles per gallon).

Design: Your client wants you to study the importance of one or both variables (Temperature and Humidity) in understanding why MPG varies (fluctuates).

Using Version 2 of the SSP, complete the following:

1. Complete all preliminary steps for correlation analysis.
2. Note that scatter plots are useful in determining patterns between two variables.  Use the scatter plot option to display the data patterns for each IV with the DV (MPG).  The name (definition) of each IV is shown right above the data.
3. Next, use the correlation option to build a correlation table for the 3 variables. Include all 3 variables in one correlation table.
4. Discuss your findings and conclusions.  Are any of the relationships (e.g., X1 with Y, X2 with Y) statistically significant?  How do you know this?  Be sure to show your work.

Using Version 3 of the SSP, complete the following:

1. Complete all preliminary steps for regression analysis.
2. Next, use the regression option to run two bi-variate regression models with MPG as the dependent variable.
3. Discuss your findings and conclusions. Does either Independent Variable you tested explain a significant amount of variation in the Dependent Variable (MPG)? Which bi-variate regression model is the strongest?
4. Finally, what will you tell your client?

Case #2: (75 points):

One of your clients is a sales manager in charge of sales territories scattered around the US. The sales manager collects data on five variables for each sales territory. They are Sales, Territory Rating, Advertising Expenditures, Number of New Accounts and Market Potential. The sales manager wants you to determine if any of the Independent Variables help to explain the level of annual sales for each of her territories.

Design: Your client wants you to study the importance of each of the Independent variables in understanding why Annual Sales vary among her sales territories.

Using Version 2 of the SSP, complete the following:

1. Complete all preliminary steps for correlation analysis.
2. Note that scatter plots are useful in determining patterns between two variables.  Use the scatter plot option to display the data patterns for each IV with the DV (Sales).  The name (definition) of each IV is shown right above the data.
3. Next, use the correlation option to build a correlation table for all 5 variables. Include all 5 variables in one correlation table.
4. Discuss your findings and conclusions.  Are any of the relationships (e.g., X1 with Y, X2 with Y, and so on) statistically significant?  How do you know this?  Be sure to show your work.

Using Version 3 of the SSP, complete the following:

1. Complete all preliminary steps for regression analysis.
2. Next, use the regression option to run a multi-variate regression model using those IVs that are statistically significant. Run as many multivariate models as necessary.
3. Discuss your findings and conclusions. Which Independent Variables successfully explained a significant amount of variation in the Dependent Variable (Sales)? How strong is the final model?
4. Finally, what will you tell your client?

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