Answer Happy

In order to help clients determine the price at which their house is likely to sell, a realtor gathered a sample of 30 purchase transactions in her area during a recent three-month period. For the response of the model, use the price of the home in thousands of dollars). As explanatory variables, use the number of square feet (also in thousands) and the number of bathrooms. Complete parts a through f. Click the icon to view the data table. .. (a) Examine scatterplots of the response versus the two explanatory variables as well as the scatterplot between the responses. Do you notice any unusual features in the data? Do the relevant plots appear straight enough for multiple regression? Examine the scatterplot to the right. Are there any unusual features in the data? 8017 O A. The scatterplot plot shows an unusual correlation. OB. The scatterplot does not have any unusual features. OC. The scatterplot does not correctly plot the data. OD. The scatterplot has leveraged outliers that should be investigated. Price ($000's) 471- 141- Sq Feet (thousands) Examine the scatterplot to the right. Are there any unusual features in the data? 8017 O A. The scatterplot plot shows an unusual correlation. O B. The scatterplot does not correctly plot the data. OC. The scatterplot has leveraged outliers that should be investigated. OD. The scatterplot does not have any unusual features. Price (5000) 471 141 Bathrooms Examine the scatterplot to the right. Are there any unusual features in the data? O A. The scatterplot does not have any unusual features. OB. The scatterplot does not correctly plot the data. OC. The scatterplot plot shows an unusual correlation. OD. The scatterplot has leveraged outliers that should be investigated. Bathrooms T35 Sq Feet (thousands)

Do the relevant plots appear straight enough for multiple regression? O A. The scatterplots appear straight, but not straight enough for multiple regression. OB. The scatterplots do not have any unusual features. OC. The scatterplots have leveraged outliers. The association appears linear and the two explanatory variables are correlated. OD. The scatterplots all appear to have no correlation. (b) Fit the multiple regression and show a summary of the estimated features of the model. Complete the table below. (Round R and se to three decimal places. Round all coefficients and standard errors to one decimal place. Round all test statistics to two decimal places. Round all probabilities to three decimal places.) R? Se Term Estimate Std Error t Ratio Prob>It| Intercept Sq Feet Bathrooms (c) Does the fitted model appear to meet the conditions for the use of the multiple regression model (MRM)? Choose the correct answer below. O A. No, the residuals are not nearly normal. OB. No, there are too many outliers. The data is not normal. OC. No, there are a substantial amount of lurking variables that have not been considered. OD. Yes, although there is concern over the effect of the leveraged outliers.

(d) Does the estimated model explain statistically significant variation in the prices of homes? What are the null and alternative hypotheses? O A. Ho: B1 * 0 or B270 HAB, = B2 = 0 OC. Ho: B2 = B2 = 0 HAB, #0 or B2 #0 OB. Ho: B, = B2 = 0 HA:B1>B2 > 0 OD. Ho: B1 = B2 = 0 HA: By <B<0 Find the F-statistic. FE (Type an integer or decimal rounded to one decimal place as needed.) Find the p-value p = (Round to three decimal places as needed.) Determine a conclusion using a level of significance of 0.05. O A. Fail to reject the null hypothesis. The p-value is not smaller than needed to assure statistical significance OB. Reject the null hypothesis. The p-value is not smaller than needed to assure statistical significance. O C. Reject the null hypothesis. The p-value is smaller than needed to assure statistical significance OD. Fail to reject the null hypothesis. The p-value is smaller than needed to assure statistical significance. (e) Compare the marginal slope for the number of bathrooms to the partial slope. Explain why these are so different, and show confidence intervals for each. (Use a 95% confidence interval.) The 95% confidence interval for the marginal slope is about - Sto sper bathroom. (Round to the nearest thousand dollars as needed.) The 95% confidence interval for the partial slope is about - $ to $ per bathroom. (Round to the nearest thousand dollars as needed.)

Explain the difference. Choose the correct answer below. O A. The ranges are different, but the estimates are comparable. The ranges change because of the correlation between variables implies a large indirect effect. O B. The ranges are comparable, but the estimates are different. The estimates change because of the correlation between variables implies a large direct effect. OC. The ranges are different, but the estimates are comparable. The estimates change because of the correlation between variables implies a large direct effect. OD. The ranges are comparable, but the estimates are different. The estimates change because of the correlation between variables implies a large indirect effect (f) A homeowner asked the realtor if she could spend $72,000 to convert a walk-in closet into a small bathroom in order to increase the sale price of her home. What does your analysis indicate? Choose the correct answer below. O A. She should do it. The price of the house after the conversion is likely to be equal to or greater than the amount spent on the conversion. OB. She should not do it. The price of the house after the conversion is not likely to be equal to or greater than the amount spent on the conversion. O C. She should do it. The price of the house after the conversion is not likely to be equal to or greater than the amount spent on the conversion OD. She should not do it. The price of the house after the conversion is likely to be equal to or greater than the amount spent on the conversion

ת | Price 485 275 388 284 274 258 408 198 356 465 523 233 209 317 400 Sq Feet 1.2 3.5 2.7 6.4 1.5 4.3 7.5 3.2 3.4 7.8 8.6 2.1 2.7 7.1 6.5 Bathrooms 3 3 2 3 4 2 4 2 2 3 5 1 1 1 2 3 Price 228 281 270 265 344 489 214 256 801 288 203 243 447 141 294 Sq. Feet 3.8 5.6 3.8 5.4 3.9 2.2 6.1 4.4 1.4 5.0 3.1 1.6 4.7 3.4 5.7 Bathrooms 1 1 2 1 1 3 1 2 1 1 1 2 2 2 2 3 WNNNN