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1. Take the above data table and copy it into MSExcel.
2. “Review of Multiple Regression”
2.1. Calculate the Correlation Matrix in Excel. Do you see any independent variables that are “closely related” or redundant? If so which variables?
2.2. From the correlation matrix which variables would you think are candidates to be removed? (none, x1,x2,x3 or x4?) Why?
3. Run the initial regression. Is the Regression Model worth keeping (Global Assessment)? Explain
4. Write the initial regression equation:
5. True or False: If the Pvalue is larger than α (i.e. 0.05) for a specific coefficient then I would eliminate the coefficient from the regression model.
6. Which individual coefficient would I remove from the model first?
7. Run the regression until you have removed the “non-significant” β coefficients. What is the final regression model?
8. What percent of the initial variability in Job Income is explained by the regression equation?
9. From the final regression model what is my expected income if I am a female with a 3.0 GPA with SAT score of 2000 and an IQ = 130?
10. How much more money would I make if I had a 150 IQ?
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