.RAR

# MBA-FP6131 Multiple Regression

In this assessment, demonstrate your proficiency in setting up, running, and interpreting multiple regression, and in communicating your results to stakeholders.

Submit two documents for this assessment.

• Use the Management Report Template (also linked in the Resources under the Capella Resources heading) to report your results. Your audience for this report are members of organizational leadership who have no background in statistics. Use the template as a guideline for structuring your management report in a way that could be easily understood by business professionals.

• Use a separate Microsoft Word document to capture your results and show your work. Paste your data from any Excel files or other sources into this document. Clearly demonstrate how you arrived at your conclusions.

• Use the information provided in the Code Book for World Data document and the World Data Excel file, both linked in the Resources under the Capella Resources heading, to complete this assessment.

Imagine Capella University's World Economy Society has engaged you to analyze data on several countries' economic and demographic indices. Particularly, you have been asked to determine predictors of a country's GDP based on the following 6 indicators: literacy rate, birth rate, death rate, life expectancy of females, life expectancy of males, and unemployment rate. Data from 114 countries with these indices are provided for you in the World Data file.

Follow the steps below to complete the regression analysis to predict GDP:

1. Explore the data for outliers. Which cases would you consider as outliers that should be removed from further analysis?

2. Determine why you should use LnGDP instead of GDP as the dependent variable in your analysis.

3. Create a scatterplot matrix of the variables, and assess linearity and normality of the variables.

4. Conduct a multiple regression using all the indicated variables to predict LnGDP.

5. Determine whether the model significantly predicts LnGDP. Explain.

6. Determine what percentage of variance in LnGDP is explained by the model.

7. Write the (i) unstandardized and (ii) standardized regression equations for LnGDP.

8. Determine which variables significantly predict LnGDP. Explain.

9. Determine which variable is the best predictor of the LnGDP. Explain.

10. Discuss the significant regression coefficients for predicting LnGDP.