Answered: The TIME output corresponding to HP can…

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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Background Information:

OBS	MAKE	MODEL	TIME	SPEED	WEIGHT	HP	HP	TIME
1	Audi	TT Roadster	8.9	133	1335	150	150	8.9
2	Mini	Cooper S	7.4	134	1240	168	168	7.4
3	Volvo	C70 T5 Sport	7.4	150	1711	220	220	7.4
4	Saab	Nine-Three	7.9	149	1680	247	247	7.9
5	Mercedes-Benz	SL350	6.6	155	1825	268	268	6.6
6	Jaguar	XK8	6.7	154	1703	290	290	6.7
7	Bugatti	Veyron 16.4	2.4	253	1950	1000	1000	2.4
8	Lotus	Exige	4.9	147	875	189	189	4.9
9	BMW	M3 (E30)	6.7	144	1257	220	220	6.7
10	BMW	330i Sport	5.9	155	1510	231	231	5.9
11	Porsche	Cayman S	5.3	171	1350	291	291	5.3
12	Nissan	Skyline GT-R (R34)	4.7	165	1560	276	276	4.7
13	Porsche	911 RS	4.7	172	1270	300	300	4.7
14	Ford	Shelby GT	5	150	1584	319	319	5
15	Mitsubishi	Evo VII RS Sprint	4.4	150	1260	320	320	4.4
16	Aston Martin	V8 Vantage	5.2	175	1630	380	380	5.2
17	Mercedes-Benz	SLK55 AMG	4.8	155	1540	355	355	4.8
18	Maserati	Quattroporte Sport GT	5.1	171	1930	394	394	5.1
19	Spyker	C8	4.5	187	1275	400	400	4.5
20	Ferrari	288GTO	4.9	189	1161	400	400	4.9
21	Mosler	MT900	3.9	190	1130	435	435	3.9
22	Lamborghini	Countach QV	4.9	180	1447	455	455	4.9
23	Chrysler	Viper GTS-R	4	190	1290	460	460	4
24	Bentley	Arnage T	5.2	179	2585	500	500	5.2
25	Ferrari	430 Scuderia	3.5	198	1350	503	503	3.5
26	Saleen	S7	3.3	240	1247	550	550	3.3
27	Lamborghini	Murcielago	4	205	1650	570	570	4
28	Pagani	Zonda F	3.6	214	1230	602	602	3.6
29	McLaren	F1	3.2	240	1140	627	627	3.2
30	Koenigsegg	CCR	3.2	242	1180	806	806	3.2

The TIME output corresponding to HP can be found as follows:

SUMMARY OUTPUT

Regression Statistics
Multiple R	0.797539769
R Square	0.636069683
Adjusted R Square	0.623072172
Standard Error	0.945077588
Observations	30

Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	7.630122482	0.40417	18.87848641	1.83E-17	6.802217	8.458028
HP	-0.00643163	0.000919	-6.99555614	1.32E-07	-0.00831	-0.00455

The fitted regression equation is:

TIMEi=7.6301-0.0064 x HPi + ei

Estimate the regression TIMEi = β0 + β1HPi + β2WEIGHTi + ε

Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	3.936870335	1.29084	3.049851421	0.004964	1.292704	6.581036
WEIGHT	0.000776715	0.000861	0.902190335	0.374652	-0.00099	0.00254

The fitted regression equation is:

TIME= 3.9369-0.00078 x WEIGHTi - ei

In an effort to determine whether going to class improved student academic performance, David Romer1 developed the following equation: ?? = ?(???? ,??? ) + ??

Where: Gi = the grade of the ith student in Romer’s class (A=4, B=3, etc).

ATTi = the percent of class lectures that the ith student attended

PSi = the percent of the problem sets that the ith student completed

1. What signs do you expect for the coefficients of the independent variables in this equation? Explain your reasoning.

2. Romer then estimated the equation:

?? ̂ = 1.07 + 1.74???? + 0.60???

? = 195, ? 2 = 0.33

Do the estimated results agree with your expectations?

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