Using the following data, conduct a linear regression analysis using an 8-step hypothesis test. In this analysis, you are testing whether SAT scores are predictive of overall college GPA. Also, write out the regression equation. Provide a brief interpretation of your results. SAT Scores GPA 670 1.2 720 1.8 750 2.3 845 1.9 960 3.0 1000 3.3 1180 3.2 1200 3.4 1370 2.9 1450 3.8 1580 4.0 1600 3.9

Using the data,  run a regression where you control for “Promotion,” and test the effect of “Wins” on “Attendance”.  Does “Promotion” have a significant effect on “Attendance”?   Wins Promotion Attendance 4 29500 36300 6 55700 40100 6 71300 41200 8 87000 53000 6 75000 44000 7 72000 45600 5 55300 39000 7 81600 47500

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The accompanying table shows a portion of data that refers to the property taxes owed by a homeowner (in $) and the size of the home (in square feet) in an affluent suburb 30 miles outside New York City. Click here for the Excel Data File Taxes Size 21,987 2,403 17,353 2,451 29,238 2,866 a. Estimate the sample regression equation that enables us to predict property Taxes on the basis of the size of the home. (Round your answers to 2 decimal places.) Taxes = + Size. b. Interpret the slope coefficient. O As Property Taxes increase by 1 dollar, the size of the house increases by 6.71 ft. O As Size increases by 1 square foot, the property taxes are predicted to increase by $6.71. c. Predict the property Taxes for a 1,400-square-foot home. (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.) Taxes

In this section, we introduced a descriptive measure of the utility of the regression equation for making predictions. a. Identify the term and symbol for that descriptive measure. b. Provide an interpretation.