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Using the data set AA #5 Q1 Fuel Economy Case.xls

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  1.   Complete the following data analysis:Please run a scatter plot for each of the two independent variables (IVs). The IVs are Temperature and Humidity. The dependent variable (DV) is “fuel economy” identified as MPG (miles per gallon).Be sure to title each scatter plot.
  2. What are your conclusions based on each of the scatter plots?
  3. Run a correlation analysis. Be sure to include all three variables in your correlation matrix.Discuss your findings. Include in your discussion, your evaluation of the strength and direction of each IV with the DV.
  4. Discuss whether the IVs are correlated with each other.
  5. What are your impressions after analyzing the correlation matrix?
  6. Run two bivariate regression models.In the first, use Temperature as the IV with MPG as the DV.
  7. In the second, use Humidity as the IV with MPG as the DV.
  • Note: In all cases, use a 90% CL. Also, be sure to follow Steps discussed in the Week 5 Study Guide and the PowerPoint slides.
  • Additional Analysis Notes:
  1. Based on your hypotheses test for the full model, what is your conclusion?
  2. Discuss whether you can continue with the regression model. If yes, find the Coefficient of Determination and discuss your findings. How much of the variation in the DV is explained by the regression model?
  3. Finally, is either regression model of practical value to the client? Defend your position.

Open the data set AA #5 Q2 Sales Management Case.xlsx

  •  This cases contains multiple Independent Variables (IVs) and one Dependent Variable (DV). Complete the data analysis as requested by the Sales Manager.Note 1: Be sure to follow each of the analysis steps in the Six-Step Process (SSP).
  • Note 2: As you did in Case #1, your analysis should include both correlation and regression analysis components.
  • Note 3: The major difference between Q #1 and this case is the number of IVs. There are 4 in this case. Thus, you will need to run one correlation analysis that includes all variables (all IVs and the DV). Based on your correlation analysis, setup and run the correct multivariate regression analysis for this case.
  • Note 4: Be sure to complete your correlation matrix using Version 2 of the SSP as a guide for your discussion.
  • Note 5: Next, run the correct multivariate regression model. Be sure to use Version 3 of the SSP as a guide for your discussion.


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  • For instance, once you get to Step 5, you will need to evaluate the hypotheses for the full model (Test #1). Next, if the model passes Test #1, you must evaluate the strength of the model (Test #2). Finally, you must proceed to Test #3, where each IV is tested for statistical significance.


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  • Note 6: Do not run any bi-variate regression models. They are not the best solution for this case analysis.
  • Note 7 Finally, in Step 6, what is your final conclusion about the final regression model? That is, what do you tell your client?
  • Note 8: Make sure you attach both files required for grading when you submit your assignment. This includes:
  1. Your Word document with your discussion of each problem.
  2. One Excel file which includes your output for Prob. 1 and your output for Prob. 2

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