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 (). m Click the icon to view the data table. PLEASE RUN SPSS OR STATCRUNCH TO OBTAIN THE REQUIRED DATA TO ANSWER THE QUESTIONS BELOWI Be prepared to RUN SPSS OR STATCRUNCH In other questions in this module tool a. State the multiple regression equation. Let X, represent the land area of the property in acres and let X age, in years. (Round to four decimal places as needed.) b. Interpret the meaning of the slopes, b; and by, in this problem. Choose the correct answer below. OA 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 bz dollars. OB. 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 1000b, dollars. OC. 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. e. Explain why the regression coefficient, bo. has no practical meaning in the context of this problem. OA. 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. OB. The interpretation of b, has no practical meaning here because it would represent the estimated age of a house with no land area and no appraised value. OC. The interpretation of bo has no practical meaning here because it would represent estimated land area of a new house with no appraised value.

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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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).
E Click the icon to view the data table.
PLEASE RUN SPSS OR STATCRUNCH TO OBTAIN THE REQUIRED DATA TO ANSWER THE QUESTIONS BELOWI Be prepared to RUN SPSS OR STATCRUNCH in other questions in this module too!
a. State the multiple regression equation. Let X1; represent the land area of the property
acres and let X2 age, in years.
(Round to four decimal places as needed.)
b. Interpret the meaning of the slopes, b; and b2, in this problem. Choose the correct answer below.
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 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 B. 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 1000b, dollars.
OC. 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
result in a decrease in appraised value by b, dollars.
c. Explain why the regression coefficient, bo, has no practical meaning in the context of this problem.
O A. The interpretation of b, has no practical meaning here because it would represent the estimated appraised value of a new house that has no land area.
O B. The interpretation of b, has no practical meaning here because it would represent the estimated age of a house with no land area and no appraised value.
Oc. The interpretation of bo has no practical meaning here because it would represent the estimated land area of a new house with no appraised value.
d. Predict the appraised value for a house that has a land area of 0.25 acres and is 55 years old.
$ thousand
(Round to two decimal places as needed.)
e. Construct a 95% confidence interval estimate for the the mean appraised value for houses that have a land area of 0.25 acres and is 55 years old.
$ thousands mean appraised value s$ thousand
(Round to one decimal place as needed.)
f. Construct a 95% prediction interval estimate for the the individual appraised value for houses that have a land area of 0.25 acres and is 55 years old.
$ thousands individual appraised value s$ thousand
(Round to one decimal place as needed.)
Transcribed Image Text: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). E Click the icon to view the data table. PLEASE RUN SPSS OR STATCRUNCH TO OBTAIN THE REQUIRED DATA TO ANSWER THE QUESTIONS BELOWI Be prepared to RUN SPSS OR STATCRUNCH in other questions in this module too! a. State the multiple regression equation. Let X1; represent the land area of the property acres and let X2 age, in years. (Round to four decimal places as needed.) b. Interpret the meaning of the slopes, b; and b2, in this problem. Choose the correct answer below. 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 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 B. 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 1000b, dollars. OC. 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 result in a decrease in appraised value by b, dollars. c. Explain why the regression coefficient, bo, has no practical meaning in the context of this problem. O A. The interpretation of b, has no practical meaning here because it would represent the estimated appraised value of a new house that has no land area. O B. The interpretation of b, has no practical meaning here because it would represent the estimated age of a house with no land area and no appraised value. Oc. The interpretation of bo has no practical meaning here because it would represent the estimated land area of a new house with no appraised value. d. Predict the appraised value for a house that has a land area of 0.25 acres and is 55 years old. $ thousand (Round to two decimal places as needed.) e. Construct a 95% confidence interval estimate for the the mean appraised value for houses that have a land area of 0.25 acres and is 55 years old. $ thousands mean appraised value s$ thousand (Round to one decimal place as needed.) f. Construct a 95% prediction interval estimate for the the individual appraised value for houses that have a land area of 0.25 acres and is 55 years old. $ thousands individual appraised value s$ thousand (Round to one decimal place as needed.)
Data Table
Appraised
Property Size
Age
Value
0.2201
0.2159
0.1633
460.1
44
363.6
53
422.6
29
540.2
0.4626
19
401.7
0.2518
41
371.1
0.2267
82
317.9
0.1867
46
744.6
0.5091
8
211.4
0.2247
58
634.3
0.1359
18
348.9
0.1724
52
351.1
0.4232
41
352.2
0.2548
45
277.9
0.1183
15
301.1
0.1684
62
285.3
0.1718
60
48
47
395.2
0.3846
612.7
0.6575
312.4
0.1721
52
365.4
0.1422
71
Print
Done
Transcribed Image Text:Data Table Appraised Property Size Age Value 0.2201 0.2159 0.1633 460.1 44 363.6 53 422.6 29 540.2 0.4626 19 401.7 0.2518 41 371.1 0.2267 82 317.9 0.1867 46 744.6 0.5091 8 211.4 0.2247 58 634.3 0.1359 18 348.9 0.1724 52 351.1 0.4232 41 352.2 0.2548 45 277.9 0.1183 15 301.1 0.1684 62 285.3 0.1718 60 48 47 395.2 0.3846 612.7 0.6575 312.4 0.1721 52 365.4 0.1422 71 Print Done
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