Regression and Correlation Responses

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RESPONSE2.xlsx
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Sheet3

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.9676426882
R Square 0.936332372
Adjusted R Square 0.9272369966
Standard Error 2.0797490989
Observations 9
ANOVA
df SS MS F Significance F
Regression 1 445.278061356 445.278061356 102.9459838701 0.0000194401
Residual 7 30.2774941995 4.3253563142
Total 8 475.5555555556
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept -3.2575406032 2.3738167503 -1.3722797275 0.2123311778 -8.8707252598 2.3556440533 -8.8707252598 2.3556440533
25 0.9642691415 0.0950371851 10.1462300324 0.0000194401 0.7395419089 1.1889963742 0.7395419089 1.1889963742
RESIDUAL OUTPUT
Observation Predicted 21 Residuals Standard Residuals
1 19.8849187935 0.1150812065 0.0591547244
2 19.8849187935 0.1150812065 0.0591547244
3 31.4561484919 -3.4561484919 -1.7765499476
4 16.9921113689 0.0078886311 0.0040549609
5 11.2064965197 0.7935034803 0.4078813655
6 12.1707656613 0.8292343387 0.4262479533
7 14.0993039443 -2.0993039443 -1.0790966653
8 20.849187935 0.150812065 0.0775213122
9 31.4561484919 3.5438515081 1.8216315723

Sheet1

Qualitative Quantitative Qualitative Qualitative Quantitative Quantitative Quantitative Quantitative SUMMARY OUTPUT
Vehicle Type/Class Year Make Model Price MPG (city) MPG (hwy) Weight (lbs)
Truck 2013 Toyota Tacoma 30,000 21 25 4,400 Regression Statistics
Truck 2021 Toyota Tacoma 28,000 20 24 4,400 Multiple R 0.9676426882
SUV 2021 Toyota 4Runner 40,000 20 24 4,800 R Square 0.936332372
Hatchback 2000 Hyundai Accent 7000 28 36 2,500 Adjusted R Square 0.9272369966
SUV 2013 Jeep Wrangler 34,000 17 21 4,000 Standard Error 2.0797490989
Coupe 1963 1/2 Ford Mustang 25,000 12 15 3,700 Observations 9
Coupe 1963 Aston Martin DB5 110,000 13 16 4,000
Coupe 1976 Porche 911 130,000 12 18 3,400 ANOVA
SUV 2018 Kia Sportage 28,000 21 25 3,300 df SS MS F Significance F
Mini Van 2021 Toyota Sienna 35,000 35 36 4,600 Regression 1 445.278061356 445.278061356 102.9459838701 0.0000194401
Residual 7 30.2774941995 4.3253563142
City mpg (y) Is there a direct correlation with City MPG with Hwy MPG? Total 8 475.5555555556
Hwy mpg(x)
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
0.9677133027 Intercept -3.2575406032 2.3738167503 -1.3722797275 0.2123311778 -8.8707252598 2.3556440533 -8.8707252598 2.3556440533
MPG(City) 0.9642691415 0.0950371851 10.1462300324 0.0000194401 0.7395419089 1.1889963742 0.7395419089 1.1889963742
0.9364690361
p value = 1.944 > .05 means we reject the correlation of the efficiency
RESIDUAL OUTPUT
Efficiency = -3.257540603+0.964269142
-2.2932714617 Regression equation Observation Predicted 21 Residuals Standard Residuals
1 19.8849187935 0.1150812065 0.0591547244
2 19.8849187935 0.1150812065 0.0591547244
3 31.4561484919 -3.4561484919 -1.7765499476
4 16.9921113689 0.0078886311 0.0040549609
5 11.2064965197 0.7935034803 0.4078813655
6 12.1707656613 0.8292343387 0.4262479533
7 14.0993039443 -2.0993039443 -1.0790966653
8 20.849187935 0.150812065 0.0775213122
9 31.4561484919 3.5438515081 1.8216315723