Question: Many variables have an impact on determining
Many variables have an impact on determining the price of a house. Among these are Living Area of the house (square feet) and number of Bathrooms. Information for a random sample of homes for sale in the Statesboro, GA, area was obtained from the Internet. Regression output modeling the asking Price with Living Area and number of Bathrooms gave the following result:
Dependent Variable is: Price
s = 67013 R-Sq = 71.1%
1. Write the regression equation.
2. Explain in context what the coefficient of Living Area means.
3. The owner of a construction firm, upon seeing this model, says that the slope for bathrooms is too small. He says that when he adds another bathroom, it increases the value by more than $9530. Can you think of an explanation for his question?
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> Recall the data we saw in Chapter 6, Exercise 3 for a bookstore. Below are data for a bookstore. The manager wants to predict Sales from Number of Sales People Working. 1. Find the slope estimate, b1 2. What does it mean, in this context? 3. Find the int
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> Here is a scatterplot of the residuals from the regression of the hard drive prices on their sizes from Exercise 6. 1. Are any assumptions or conditions violated? If so, which ones? 2. What would you recommend about this regression?
> Here are residual plots (residuals plotted against predicted values) for three linear regression models. Indicate which condition appears to be violated (Linearity, Outlier, or Equal Spread) in each case.
> For the hard drive data of Exercise 6, find and interpret the value of R2.
> For the regression model for the bookstore of Exercise 5, what is the value of R2 and what does it mean?
> Here are the residuals for a regression of Price on Capacity for the hard drives of Exercise 6 (based on the hand-computed coefficients). 1. Which residual contributes the most to the sum that is minimized by the least squares criterion? 2. Five of the r
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> A larger firm is considering acquiring the bookstore of Exercise 3. An analyst for the firm, noting the relationship seen in Exercise 3, suggests that when they acquire the store they should hire more people because that will drive higher sales. Is his c
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> If we assume that the conditions for correlation are met, which of the following are true? If false, explain briefly. 1. A correlation of 0.98 indicates a strong, negative association. 2. Multiplying every value of x by 2 will double the correlation. 3.
