ý = - 0.00834'x+ 47.71 (Round the x coefficient to five decimal places as needed. Round the constant to two decimal places as needed.)
ý = - 0.00834'x+ 47.71 (Round the x coefficient to five decimal places as needed. Round the constant to two decimal places as needed.)
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
Easy Step by step of how to solve this type of problem.
Transcribed Image Text: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.
E Click here to view the weight and gas mileage data.
(a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.
ý = - 0.00834'x + 47.71)
(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. A weightless car will get
miles per gallon, on average. It is not appropriate to interpret the slope.
GB. For every pound added to the weight of the car, gas mileage in the city will decrease by 0.00834 mile(s) per gallon, on average. It is not appropriate to
interpret the y-intercept.
O C. For every pound added to the weight of the car, gas mileage in the city will decrease by
mile(s) per gallon, on average. A weightless car will get
miles per gallon, on average.
O D. It is not appropriate to interpret the slope or the y-intercept.
(c) A certain gas-powered car weighs 3500 pounds and gets 17 miles per gallon. Is the miles per gallon of this car above average or below average for cars of this
weight?
O 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?
O A. Yes, because the hybrid is partially powered by gas.
O B. Yes, because the absolute value of the correlation coefficient is greater than the critical value for a sample size of n = 11.
Oc. No, because the hybrid is a different type of car.
O D. 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
Miles per
Gallon, y
3639
18
3845
17
2700
26
3506
18
3263
20
2866
24
3703
16
2680
25
3430
20
3747
16
3386
18
Print
Done
Expert Solution
Working
| X | Y | (x-xbar) | (x-xbar)^2 | (y-ybar) | (y-ybar)^2 | (x-xbar)*(y-ybar) |
| 3639 | 18 | 296.727 | 88047.074 | -1.818 | 3.306 | -539.504 |
| 3845 | 17 | 502.727 | 252734.711 | -2.818 | 7.942 | -1416.777 |
| 2700 | 26 | -642.273 | 412514.256 | 6.182 | 38.215 | -3970.413 |
| 3506 | 18 | 163.727 | 26806.620 | -1.818 | 3.306 | -297.686 |
| 3263 | 20 | -79.273 | 6284.165 | 0.182 | 0.033 | -14.413 |
| 2866 | 24 | -476.273 | 226835.711 | 4.182 | 17.488 | -1991.686 |
| 3703 | 16 | 360.727 | 130124.165 | -3.818 | 14.579 | -1377.322 |
| 2680 | 25 | -662.273 | 438605.165 | 5.182 | 26.851 | -3431.777 |
| 3430 | 20 | 87.727 | 7696.074 | 0.182 | 0.033 | 15.950 |
| 3747 | 16 | 404.727 | 163804.165 | -3.818 | 14.579 | -1545.322 |
| 3386 | 18 | 43.727 | 1912.074 | -1.818 | 3.306 | -79.504 |
Step by step
Solved in 2 steps with 8 images
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Recommended textbooks for you
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman