Data Table
parts (a) through (f).
Click the icon to view the data table.
module tool
a. State the multiple regression equation. Let x_(1), represent the land area of the property in acres and let x_(2), age, in years.
(Round to four decimal places as needed.)
b. Interpret the meaning of the slopes, b_(1) and b_(2), in this problem. Choose the correct answer below.
to result in a decrease in appraised value by b_(1) dollars.
to result in a decrease in appraised value by b_(2) dollars.
estimated to result in a decrease in appraised value by 1000b_(2) dollars.
c. Explain why the regression coefficient, b_(0), has no practical meaning in the context of this problem.
A. The interpretation of b_(0) has no practical meaning here because it would represent the estimated age of a house with no land area and no appraised value.
B. The interpretation of b_(0) has no practical meaning here because it would represent the estimated land area of a new house with no appraised value.
C. The interpretation of b_(0) has no practical meaning here because it would represent the estimated appraised value of a new house that has no land area.
d. Predict the appraised value for a house that has a land area of 0.35 acres and is 50 years old.
Data Table
Appraised Property Size Value 467.6 0.2252 360.2 0.2116 423.3 0.1689 546.2 0.4646 402.7 0.2537 375.3 0.2249 310.2 0.1839 748.8 0.5033 210.8 0.2228 634.2 0.1316 345.7 0.1785 350.2 0.4259 357.6 0.2569 270.2 0.1107 308.6 0.1601 288.8 0.1701 392.1 0.3832 619.2 0.6555 312.7 0.1773 368.7 0.1487
Age 46 50 24 11 47 80 44 5 60 15 54 40 47 14 69 50 48 48 54 80
A certain town is located approximately 25 miles east of a large city. The data organized below include the appraised value (in thousands of dollars), land area of the property in acres, and age, in years, for a sample of 20 single-family homes located in the town. Develop a multiple linear regression model to predict appraised value based on land area of the property and age, in years. Complete parts (a) through (f). Click the icon to viow the data table.
PLEASE RUN 3FS3 OR STATCRUNCH TO OBTAIN THE REQUIRED DATA TO ANSWER THE QUESTIONS BELOW! Be prepured to RUN SPSS OR STATCRUNCH in other queution3 in this module too!
=+X+X (Round to four decimal places as needed.)
O A. For a given age, each increase of 1 acre in land area is estimated to result in an increase in appraised value by bz dollars. For a given land area, each increase in one year in age is estimated to result in a decrease in appraised value by b, dollars.
O B. For a given age,each increase of 1 acre in land area is estimated to result in an increase in appraised value by b, dollars. For a given land area, each increase in one year in age is estimated
to result in a decrease in appraised value by b, dollars.
O C. For a given age, each increase of 1 acre in land area is estimated to result in an increase in appraised value by 1000b, dollars. For a given land area, each increase in one year in age is estimated to result in a decrease in appraised value by 1000b2 dollars.
c. Explain why the regression coefficient, bo, has no practical meaning in the context of this problem.
O A. The interpretation of bo has no practical meaning here because it would represent the estimated age of a house with no land area and no appraised value
O B. The interpretation of b, has no practical meaning here because it would represent the estimated land area of a new house with no appraised value.
O C. The interpretation of bo has no practical meaning here because it would represent the estimated appraised value of a new house that has no land area.
d. Predict the appraised value for a house that has a land area of 0.35 acres and is 50 years old
