Question: You want to develop a model to predict the assessed value of houses, based on heating area. A sample of 15 single-family houses is selected in a city. The assessed value (in thousands of dollars) and the heating area of the houses (in thousands of square feet) are recorded. The data are in the Excel file, HOUSE2.xls (CD/browse/Excel Data Files/).

1. Set up a scatter diagram.
2. Assuming a linear relationship, find the regression coefficients, b ₀ , b ₁ , and its regression equation.
3. Interpret the meaning of the Y-intercept b _o , and the slope b ₁ in this problem.
4. Predict the assessed value for a house whose heating area is 1,750 square feet.
5. Determine the coefficient of determination, r ² , and interpret its meaning.
6. Find the standard error of the estimate.
7. Perform a residual analysis on your results and determine the adequacy of the fit of the model.
8. At the 0.05 level of significance, is there evidence of a linear relationship between assessed value and heating area?
9. Set up a 95% confidence interval estimate of the population slope,  ₁ .
10. Set up a 95% confidence interval estimate of the assessed value of an individual house with a heating area of 1,750 square feet.

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Solution: The downloadable solution consists of 7 pages
Deliverable: Word Document