What is the slope coefficient for the horsepower variable? Is this coefficient significant at 5% level of significance (alpha=0.05)?

Trigonometry (MindTap Course List)
8th Edition
ISBN:9781305652224
Author:Charles P. McKeague, Mark D. Turner
Publisher:Charles P. McKeague, Mark D. Turner
Chapter4: Graphing And Inverse Functions
Section: Chapter Questions
Problem 6GP: If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use...
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What is the slope coefficient for the horsepower variable? Is this coefficient significant at 5% level of significance (alpha=0.05)?

OLS Regression Results
R-squared:
Adj. R-squared:
Dep. Variable:
0.821
mpg
OLS
Model:
0.808
Method:
Least Squares
F-statistic:
61.98
Prob (F-statistic) :
Log-Likelihood:
Date:
Wed, 07 Oct 2020
8.10e-11
Time:
11:19:54
-70.463
No. Observations:
30
AIC:
146.9
Df Residuals:
27
BIC:
151.1
Df Model:
2
Covariance Type:
nonrobust
coef
std err
P>lt|
[0.025
0.975]
Intercept
37.1838
1.650
22.540
0.000
33.799
40.569
wt
-3.8810
0.658
-5.902
0.000
-5.230
-2.532
hp
-0.0309
0.010
-3.201
0.003
-0.051
-0.011
Omnibus:
4.159
Durbin-Watson:
2.606
Prob (Omnibus) :
0.125
3.100
Jarque-Bera (JB) :
Prob (JB) :
Skew:
0.784
0.212
Kurtosis:
3.147
Cond. No.
561.
Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
Transcribed Image Text:OLS Regression Results R-squared: Adj. R-squared: Dep. Variable: 0.821 mpg OLS Model: 0.808 Method: Least Squares F-statistic: 61.98 Prob (F-statistic) : Log-Likelihood: Date: Wed, 07 Oct 2020 8.10e-11 Time: 11:19:54 -70.463 No. Observations: 30 AIC: 146.9 Df Residuals: 27 BIC: 151.1 Df Model: 2 Covariance Type: nonrobust coef std err P>lt| [0.025 0.975] Intercept 37.1838 1.650 22.540 0.000 33.799 40.569 wt -3.8810 0.658 -5.902 0.000 -5.230 -2.532 hp -0.0309 0.010 -3.201 0.003 -0.051 -0.011 Omnibus: 4.159 Durbin-Watson: 2.606 Prob (Omnibus) : 0.125 3.100 Jarque-Bera (JB) : Prob (JB) : Skew: 0.784 0.212 Kurtosis: 3.147 Cond. No. 561. Warnings: [1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
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