# Question: Seattle Home Prices This data table expands the data introduced

Seattle Home Prices This data table expands the data introduced in Chapter 19 on the prices of homes in the Seattle area. One realtor operating in Seattle listed all 28 homes for sale in the original data table. This table includes prices and sizes of 8 more homes listed by a different realtor in Seattle. As previously, we’ll look at the price per square foot, using the recip- rocal of the number of square feet as the explanatory marginal. In this model, the intercept estimates the variable cost per square foot and the slope of 1/Sq Fit estimates the fixed costs present regardless of the size of the home.

(a) Create a scatterplot of the cost per square foot of the homes on the reciprocal of the size of the homes. Do you see a difference in the relation- ship between cost per square foot and 1>Sq Fit for the two realtors? Use color-coding or different symbols to distinguish the data for the two realtors.

(b) Based on your visual impression formed in part (a), fit an appropriate regression model that describes the fixed and marginal costs for these realtors. Use a dummy variable coded as + for Realtor B to represent the different realtors in the regression.

(c) Does the estimated multiple regression fit in part

(b) Meet the conditions for the MRM?

(d) Interpret the estimated coefficients from the equation fit in part (b), if it is Okay to do so. If not, indicate why not. What does the fitted model tell you about the properties offered by the realtors?

(e) Would it be appropriate to use the estimated standard errors shown in the output of your regression estimated in part (b) to set confidence intervals for the estimated intercept and slopes? Explain.

(a) Create a scatterplot of the cost per square foot of the homes on the reciprocal of the size of the homes. Do you see a difference in the relation- ship between cost per square foot and 1>Sq Fit for the two realtors? Use color-coding or different symbols to distinguish the data for the two realtors.

(b) Based on your visual impression formed in part (a), fit an appropriate regression model that describes the fixed and marginal costs for these realtors. Use a dummy variable coded as + for Realtor B to represent the different realtors in the regression.

(c) Does the estimated multiple regression fit in part

(b) Meet the conditions for the MRM?

(d) Interpret the estimated coefficients from the equation fit in part (b), if it is Okay to do so. If not, indicate why not. What does the fitted model tell you about the properties offered by the realtors?

(e) Would it be appropriate to use the estimated standard errors shown in the output of your regression estimated in part (b) to set confidence intervals for the estimated intercept and slopes? Explain.

## Answer to relevant Questions

Leases (introduced in Chapter 19) This data table includes the annual prices of 223 commercial leases. All of these leases provide office space in a Midwestern city in the United States. In previous exercises, we estimated ...Promotion (introduced in Chapter 19) These data describe spending by a pharmaceutical company to promote a cholesterol-lowering drug. The data cover 39 consecutive weeks and isolate the metropolitan areas near Boston, ...Does the p-value of the two-sample t-test that does not assume equal variances match the p-value of the slope on a regression of Y on a dummy variable? A line of men’s shirts was offered in a chain of retail stores at three prices: $32, $35, and $40. Weekly sales were monitored, producing totals at 30 stores in the chain (10 at each price). Which produces a higher R2: a ...An overnight shipping firm operates major sorting facilities (hubs) in six cities. To compare the performance of the hubs, it tracked the shipping time (in hours) required to process 20 randomly selected priority packages as ...Post your question