Real Estate Statistics
QNT351~WK5 Individual Assignment: Real Estate Data DUE SUNDAY, MAY 21st
Resources: Appendix A1 at the end of Basic Statistics for Business and Economics (See attached Chapters 10 & 13 to answer questions below)
QUESTION #1:
Answer question 58 in the Data Set Exercises from Ch. 10 of Basic Statistics for Business and Economics.
Exercise #58: Refer to the Real Estate data, which report information on homes sold in Phoenix, Arizona, last year.
a. A recent article in The Arizona Republic indicated that the mean selling price of the homes in the area is more than $220,000. Can we conclude that the mean selling price in the Denver area is more than $220,000? Use the .01 significance level. What is the p-value?
ANSWER: …show more content…
b. The same article reported the mean size was more than 2,100 square feet. Can we conclude that the mean size of homes sold in the Denver area is more than 2,100 square feet? Use the .01 significance level. What is the p-value?
ANSWER:
c.
Determine the proportion of homes that have an attached garage. At the .05 significance level can we conclude that more than 60 percent of the homes sold in the Denver area had an attached garage? What is the p-value?
ANSWER:
d. Determine the proportion of homes that have a pool. At the .05 significance level, can we conclude that less than 40 percent of the homes sold in the Denver area had a pool? What is the p-value?
ANSWER:
QUESTION #2:
Answer question 62 in the Data Set Exercises from Ch. 13 of Basic Statistics for Business and Economics.
Exercise #62: Refer to the Real Estate data, which report information on homes sold in Phoenix, Arizona, last year.
a. Let selling price be the dependent variable and size of the home the independent variable. Determine the regression equation. Estimate the selling price for a home with an area of 2,200 square feet. Determine the 95 percent confidence interval and the 95 percent prediction interval for the selling price of a home with 2,200 square feet.
ANSWER:
b. Let selling price be the dependent variable and distance from the center of the city the independent variable. Determine the regression equation. Estimate the selling price of a home 20 miles from the center of the city. Determine the 95 percent confidence interval and the 95 percent prediction interval for homes 20 miles from the center of the
city.
ANSWER:
c. Can you conclude that the independent variables “distance from the center of the city” and “selling price” are negatively correlated and that the area of the home and the selling price are positively correlated? Use the .05 significance level. Report the p-value of the test.
ANSWER:
Resources: Appendix A1 at the end of Basic Statistics for Business and Economics (See attached Chapters 10 & 13 to answer questions below)
QUESTION #1:
Answer question 58 in the Data Set Exercises from Ch. 10 of Basic Statistics for Business and Economics.
Exercise #58: Refer to the Real Estate data, which report information on homes sold in Phoenix, Arizona, last year.
a. A recent article in The Arizona Republic indicated that the mean selling price of the homes in the area is more than $220,000. Can we conclude that the mean selling price in the Denver area is more than $220,000? Use the .01 significance level. What is the p-value?
ANSWER: …show more content…
b. The same article reported the mean size was more than 2,100 square feet. Can we conclude that the mean size of homes sold in the Denver area is more than 2,100 square feet? Use the .01 significance level. What is the p-value?
ANSWER:
c.
Determine the proportion of homes that have an attached garage. At the .05 significance level can we conclude that more than 60 percent of the homes sold in the Denver area had an attached garage? What is the p-value?
ANSWER:
d. Determine the proportion of homes that have a pool. At the .05 significance level, can we conclude that less than 40 percent of the homes sold in the Denver area had a pool? What is the p-value?
ANSWER:
QUESTION #2:
Answer question 62 in the Data Set Exercises from Ch. 13 of Basic Statistics for Business and Economics.
Exercise #62: Refer to the Real Estate data, which report information on homes sold in Phoenix, Arizona, last year.
a. Let selling price be the dependent variable and size of the home the independent variable. Determine the regression equation. Estimate the selling price for a home with an area of 2,200 square feet. Determine the 95 percent confidence interval and the 95 percent prediction interval for the selling price of a home with 2,200 square feet.
ANSWER:
b. Let selling price be the dependent variable and distance from the center of the city the independent variable. Determine the regression equation. Estimate the selling price of a home 20 miles from the center of the city. Determine the 95 percent confidence interval and the 95 percent prediction interval for homes 20 miles from the center of the
city.
ANSWER:
c. Can you conclude that the independent variables “distance from the center of the city” and “selling price” are negatively correlated and that the area of the home and the selling price are positively correlated? Use the .05 significance level. Report the p-value of the test.
ANSWER: