K An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) through (d) below. (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. y=x+ (Round the x coefficient to five decimal places as needed. Round the constant to two decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice. (Use the answer from part a to find this answer.) OA. For every pound added to the weight of the car, gas mileage in the city will decrease by on average. It is not appropriate to interpret the y-intercept. B. A weightless car will get miles per gallon, on average. It is not appropriate to interpret the slope. mile(s) per gallon, C. For every pound added to the weight of the car, gas mileage in the city will decrease by on average. A weightless car will get miles per gallon, on average. OD. It is not appropriate to interpret the slope or the y-intercept. mile(s) per gallon, (c) A certain gas-powered car weighs 3600 pounds and gets 16 miles per gallon. Is the miles per gallon of this car above average or below average for cars of this weight? Above Below (d) Would it be reasonable to use the least-squares regression line to predict the miles per gallon of a hybrid gas and electric car? Why or why not? OA. Yes, because the absolute value of the correlation coefficient is greater than the critical value for a sample size of n = 11. B. No, because the absolute value of the correlation coefficient is less than the critical value for a sample size of n = 11.
K An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) through (d) below. (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. y=x+ (Round the x coefficient to five decimal places as needed. Round the constant to two decimal places as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice. (Use the answer from part a to find this answer.) OA. For every pound added to the weight of the car, gas mileage in the city will decrease by on average. It is not appropriate to interpret the y-intercept. B. A weightless car will get miles per gallon, on average. It is not appropriate to interpret the slope. mile(s) per gallon, C. For every pound added to the weight of the car, gas mileage in the city will decrease by on average. A weightless car will get miles per gallon, on average. OD. It is not appropriate to interpret the slope or the y-intercept. mile(s) per gallon, (c) A certain gas-powered car weighs 3600 pounds and gets 16 miles per gallon. Is the miles per gallon of this car above average or below average for cars of this weight? Above Below (d) Would it be reasonable to use the least-squares regression line to predict the miles per gallon of a hybrid gas and electric car? Why or why not? OA. Yes, because the absolute value of the correlation coefficient is greater than the critical value for a sample size of n = 11. B. No, because the absolute value of the correlation coefficient is less than the critical value for a sample size of n = 11.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Transcribed Image Text:1:30
K
An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying
data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model
year. Complete parts (a) through (d) below.
(a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the
response variable.
ŷ=x+
(Round the x coefficient to five decimal places as needed. Round the constant to two decimal places as needed.)
(b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in
your choice.
(Use the answer from part a to find this answer.)
O A. For every pound added to the weight of the car, gas mileage in the city will decrease by
on average. It is not appropriate to interpret the y-intercept.
B.
A weightless car will get miles per gallon, on average. It is not appropriate to interpret the slope.
mile(s) per gallon,
O C. For every pound added to the weight of the car, gas mileage in the city will decrease by
on average. A weightless car will get miles per gallon, on average.
OD. It is not appropriate to interpret the slope or the y-intercept.
Above
Below
(c) A certain gas-powered car weighs 3600 pounds and gets 16 miles per gallon. Is the miles per gallon of this car
above average or below average for cars of this weight?
(d) Would it be reasonable to use the least-squares regression line to predict the miles per gallon of a hybrid gas and
electric car? Why or why not?
OA. Yes, because the absolute value of the correlation coefficient is greater than the critical value for a sample
size of n = 11.
|||
B. No, because the absolute value of the correlation coefficient is less than the critical value for a sample size
of n = 11.
Car Weight and MPG
=
Weight
(pounds), x
3671
3847
2818
3645
3308
3010
3819
2527
3411
3778
3341
Print
Miles per
Gallon, y
16
15
25
ONNENDE
1
2.4G 13%
19
22
22
16
24
19
18
18
mile(s) per gallon,
Done
D
O
X
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