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County assessors use computerized systems to value single-family residential properties for property tax purposes. Given below are the data on lot size (in acres) and assessed value (in thousands of dollars) for a sample of homes in an area. Complete parts (a) through (f). Click the icon to view the data. a. Graph the data points. O A. Value ($1000) 800- 700- 600- 500- 400- 300- 200+ 1 2 3 Lot Size (acres Value ($1000) B. 800- 700- 600- 500- 400- 300- 200+ 194 O C. 2 3 Lot Size (acres Value ($1000) 800- 700- 600- 500- 400- 300- 200 1 2 Lot Size (acres D. Value ($1000) 800- 700+ 600- 500- 400- 300- 200+ 1 b. Decide whether finding a regression line for the data is reasonable. There is to the data, so it is a linear renrassinn 2 3 Lot Size (acret to carry out

County assessors use computerized systems to value single-family residential properties for property tax purposes. Given below are the data on lot size (in acres) and assessed value (in thousands of dollars) for a sample of homes in an area. Complete parts (a) through (f). Click the icon to view the data. a. Graph the data points. O A. Value ($1000) 800- 700- 600- 500- 400- 300- 200+ 1 2 3 Lot Size (acres Value ($1000) B. 800- 700- 600- 500- 400- 300- 200+ 194 O C. 2 3 Lot Size (acres Value ($1000) 800- 700- 600- 500- 400- 300- 200 1 2 Lot Size (acres D. Value ($1000) 800- 700+ 600- 500- 400- 300- 200+ 1 b. Decide whether finding a regression line for the data is reasonable. There is to the data, so it is a linear renrassinn 2 3 Lot Size (acret to carry out

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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If finding a regression line for the data is​ reasonable, then find the regression equation for the data points. Select the correct choice below and fill in any answer boxes within your choice.
 
 
A.
y=enter your response here+enter your response herex
​(Round to two decimal places as​ needed.)
 
B.
Not applicable since a regression line for the data is not reasonable
 
d. If finding a regression line for the data is​ reasonable, then identify any outliers and potential influential observations.
 
 
A.
There is at least one outlier and at least one influential observation.
 
B.
There are no outliers and there is one influential observation.
 
C.
There is one outlier and there are no influential observations.
 
D.
There are no outliers and no influential observations.
 
E.
Not applicable since a regression line for the data is not reasonable
 
e. If finding a regression line for the data is​ reasonable, then
in
case a potential outlier is​ present, remove it and discuss the effect. Select the correct choice below and fill in any answer boxes within your choice.
 
 
A.
After removing the​ outlier(s), the regression line is
y=enter your response here+enter your response here​x,
which is approximately the same as the original regression line.
​(Round to two decimal places as​ needed.)
 
B.
After removing the​ outlier(s), the regression line is
y=enter your response here+enter your response here​x,
which is significantly different from the original regression line.
​(Round to two decimal places as​ needed.)
 
C.
There are no outliers.
 
D.
Not applicable since a regression line for the data is not reasonable
 
f. If finding a regression line for the data is​ reasonable, then
in
case a potential influential observation is​ present, remove it and discuss the effect. Select the correct choice below and fill in any answer boxes within your choice.
 
 
A.
After removing the influential​ observation(s), the regression line is
y=enter your response here+enter your response here​x,
which is significantly different from the original regression line.
​(Round to two decimal places as​ needed.)
 
B.
After removing the influential​ observation(s), the regression line is
y=enter your response here+enter your response here​x,
which is approximately the same as the original regression line.
​(Round to two decimal places as​ needed.)
 
C.
There are no influential observations.
 
D.
Not applicable since a regression line for the data is not reasonable
County assessors use computerized systems to value single-family residential properties for property tax purposes. Given below are the data on lot size (in acres) and assessed value (in thousands of dollars) for a sample of homes in an area. Complete parts (a) through (f). Click the icon to view the data. a. Graph the data points. O A. Value ($1000) 800- 700- 600- 500 400- 300- 200+ 1 2 Lot Size (acres B. There is a linear regression Value ($1000) 800- 700- 600- 500- 400- 300- 200+ 1 O C. 2 3 Lot Size (acres Value ($1000) 800- 700- 600- 500- 400- 300- 200+ 1 2 3 Lot Size (acres O D. Value ($1000) 800- 700- 600- 500- 400- 300- 200+ 1 b. Decide whether finding a regression line for the data is reasonable. to the data, so it is 2 3 Lot Size (acres to carry out
Transcribed Image Text:County assessors use computerized systems to value single-family residential properties for property tax purposes. Given below are the data on lot size (in acres) and assessed value (in thousands of dollars) for a sample of homes in an area. Complete parts (a) through (f). Click the icon to view the data. a. Graph the data points. O A. Value ($1000) 800- 700- 600- 500 400- 300- 200+ 1 2 Lot Size (acres B. There is a linear regression Value ($1000) 800- 700- 600- 500- 400- 300- 200+ 1 O C. 2 3 Lot Size (acres Value ($1000) 800- 700- 600- 500- 400- 300- 200+ 1 2 3 Lot Size (acres O D. Value ($1000) 800- 700- 600- 500- 400- 300- 200+ 1 b. Decide whether finding a regression line for the data is reasonable. to the data, so it is 2 3 Lot Size (acres to carry out
Lot Size and Value Lot Size 2.37 2.09 2.21 2.21 2.10 2.06 2.03 2.44 2.14 2.63 2.02 2.09 2.98 2.05 2.17 2.18 2.13 Value 400 355 582 262 637 271 284 738 550 331 415 381 442 611 387 332 203 Print Lot Size 2.58 2.02 2.05 2.09 2.32 2.02 2.90 2.20 2.03 2.00 2.01 2.63 2.95 2.08 2.28 2.09 2.61 Done Value 328 308 388 466 687 319 650 305 541 520 600 512 719 379 323 479 475 - X
Transcribed Image Text:Lot Size and Value Lot Size 2.37 2.09 2.21 2.21 2.10 2.06 2.03 2.44 2.14 2.63 2.02 2.09 2.98 2.05 2.17 2.18 2.13 Value 400 355 582 262 637 271 284 738 550 331 415 381 442 611 387 332 203 Print Lot Size 2.58 2.02 2.05 2.09 2.32 2.02 2.90 2.20 2.03 2.00 2.01 2.63 2.95 2.08 2.28 2.09 2.61 Done Value 328 308 388 466 687 319 650 305 541 520 600 512 719 379 323 479 475 - X
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