The cases that make up this dataset are types of cars. The data include the engine size or displacement (in liters) and horsepower (HP) of 67 vehicles sold in a certain country in 2011. Use the SRM of the horsepower on the engine displacement to complete parts (a) through (c). E Click the icon to view the data table. (a) A manufacturer offers 2.0 and 2.6 liter engines in a particular model car. Based on these data, how much more horsepower should one expect the larger engine to produce? Give your answer as a 95% confidence interval. | to (Round to the nearest integer as needed.) (b) Do you have any qualms about presenting this interval as an appropriate 95% range? O A. Yes, because the p-value for the two-sided hypothesis B, =0 is too high. O B. Yes, because there are several outliers in the data and they will have to be removed. O C. Yes, because the value of r is too low. O D. No (c) Based on the fit of this regression model, what is the expected horsepower of a car with a 2.6 liter engine? Give your answer as a 95% prediction interval. Do you think that the standard prediction interval is reasonable? Explain. What is the expected horsepower of a car with a 2.6 liter engine using a 95% prediction interval? | to| (Round to the nearest integer as needed.) Do you think that the standard prediction interval is reasonable? Explain. O A. Yes, because the residuals of the regression are approximately normally distributed. O B. Yes, because approximately the same number of data points are above and below the regression line. OC. No, because a fan-shaped pattern occurs in the data points around the regression line and the regression line overpredicts the horsepower for smaller displacement engines. O D. No, because even though the residuals of the regression are approximately normally distributed, the regression line underpredicts the horsepower for smaller displacement engines.

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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Displacement (liters)	Horsepower
4.2	417
5.2	535
3.1	341
4.2	349
1.9	202
1.9	270
2.9	227
3.1	296
4.2	390
2.1	320
3.9	419
1.7	124
1.6	178
4.5	562
2.3	169
2.5	174
2.6	223
2.1	144
2.5	296
3.5	262
6.5	297
1.9	237
3.9	296
3.5	304
5.2	403
5.2	565
3.6	267
3.1	262
6.1	422
2.4	185
1.5	88
1.8	139
1.5	92
1.4	119
3.5	296
3.6	286
3.6	303
2.4	207
3.6	288
3.5	296
1.5	141
1.9	141
1.9	147
4.9	428
2.1	210
3.6	308
3.8	340
2.1	281
1.9	213
2.7	300
1.6	97
2.1	146
2.6	163
2.5	168
2.3	271
1.9	168
1.3	96
2.6	156
3.9	239
2.4	182
1.5	103
6.1	515
2.4	173
1.9	199
1.9	143
1.9	113
3.4	288

The cases that make up this dataset are types of cars. The data include the engine size or displacement (in liters) and horsepower (HP) of 67 vehicles sold in a certain country in 2011. Use the SRM of the horsepower on the engine displacement to
complete parts (a) through (c).
E Click the icon to view the data table.
(a) A manufacturer offers 2.0 and 2.6 liter engines in a particular model car. Based on these data, how much more horsepower should one expect the larger engine to produce? Give your answer as a 95% confidence interval.
| to
(Round to the nearest integer as needed.)
(b) Do you have any qualms about presenting this interval as an appropriate 95% range?
O A. Yes, because the p-value for the two-sided hypothesis B, = 0 is too high.
O B. Yes, because there are several outliers in the data and they will have to be removed.
O C. Yes, because the value of r2 is too low.
O D. No
(c) Based on the fit of this regression model, what is the expected horsepower of a car with a 2.6 liter engine? Give your answer as a 95% prediction interval. Do you think that the standard prediction interval is reasonable? Explain.
What is the expected horsepower of a car with a 2.6 liter engine using a 95% prediction interval?
| to| (Round to the nearest integer as needed.)
Do you think that the standard prediction interval is reasonable? Explain.
O A. Yes, because the residuals of the regression are approximately normally distributed.
O B. Yes, because approximately the same number of data points are above and below the regression line.
OC. No, because a fan-shaped pattern occurs in the data points around the regression line and the regression line overpredicts the horsepower for smaller displacement engines.
O D. No, because even though the residuals of the regression are approximately normally distributed, the regression line underpredicts the horsepower for smaller displacement engines.

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