DATA BELOW A.What is the expected effect of increasing horsepower on 0-60 time?
ID: 2923133 • Letter: D
Question
DATA BELOW
A.What is the expected effect of increasing horsepower on 0-60 time?
B. Using Excel, create a scatter plot of TIME (dependent variable, y-axis) and HP (independent variable, x-axis). Add a linear trendline to your scatter plot. Does your scatter plot confirm your prediction in (a)?
C. Estimate the regression TIMEi = 0 + 1HPi +
D. Interpret your estimated coefficient on HP. (That is, in words, what does the value tell you?) Interpret the R2 from your regression.
E. Estimate the regression TIMEi = 0 + 1HPi + 2WEIGHTi +
F. Interpret your estimated coefficient on WEIGHT. (That is, in words, what does the value tell you?) Does the sign of this coefficient match your expectations? What happened to the adjusted R2 when WEIGHT was added to this regression? What does this tell you?
OBS MAKE MODEL TIME SPEED WEIGHT HP 1 Audi TT Roadster 8.9 133 1335 150 2 Mini Cooper S 7.4 134 1240 168 3 Volvo C70 T5 Sport 7.4 150 1711 220 4 Saab Nine-Three 7.9 149 1680 247 5 Mercedes-Benz SL350 6.6 155 1825 268 6 Jaguar XK8 6.7 154 1703 290 7 Bugatti Veyron 16.4 2.4 253 1950 1000 8 Lotus Exige 4.9 147 875 189 9 BMW M3 (E30) 6.7 144 1257 220 10 BMW 330i Sport 5.9 155 1510 231 11 Porsche Cayman S 5.3 171 1350 291 12 Nissan Skyline GT-R (R34) 4.7 165 1560 276 13 Porsche 911 RS 4.7 172 1270 300 14 Ford Shelby GT 5 150 1584 319 15 Mitsubishi Evo VII RS Sprint 4.4 150 1260 320 16 Aston Martin V8 Vantage 5.2 175 1630 380 17 Mercedes-Benz SLK55 AMG 4.8 155 1540 355 18 Maserati Quattroporte Sport GT 5.1 171 1930 394 19 Spyker C8 4.5 187 1275 400 20 Ferrari 288GTO 4.9 189 1161 400 21 Mosler MT900 3.9 190 1130 435 22 Lamborghini Countach QV 4.9 180 1447 455 23 Chrysler Viper GTS-R 4 190 1290 460 24 Bentley Arnage T 5.2 179 2585 500 25 Ferrari 430 Scuderia 3.5 198 1350 503 26 Saleen S7 3.3 240 1247 550 27 Lamborghini Murcielago 4 205 1650 570 28 Pagani Zonda F 3.6 214 1230 602 29 McLaren F1 3.2 240 1140 627 30 Koenigsegg CCR 3.2 242 1180 806Explanation / Answer
A.
B.
C. Estimate the regression is
TIme = 7.63 - 0.0064HP
D.
Interpretation of the slope: If the horsepower is increases by 1 then the model predicts that time is will decrease by approximately 0.0064
Interpretation of the intercept: If the horsepower is increases by 0 then the model predicts that time will increase by approximately 7.63
R2 =0.6360 means that 63.60% of the variation in your HP variable can be explained a linear relationship with the time variable.
E.
Time = 5.88+0.00126 Weight -0.0067HP
F. If the weight is increases by 1 then the model predicts that time will increase by approximately 0.00126
Yes this improve the relationship.
Adjusted R2 squared tells us that 68.86% of the variation in your variables (Weight and HP) can be explained a linear relationship with the time variable. It give more linear model as compare to previous.
SUMMARY OUTPUT Regression Statistics Multiple R 0.79754 R Square 0.63607 Adjusted R Square 0.623072 Standard Error 0.945078 Observations 30 ANOVA df SS MS F Significance F Regression 1 43.70986 43.70986 48.93781 1.32E-07 Residual 28 25.00881 0.893172 Total 29 68.71867 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 7.630122 0.40417 18.87849 1.83E-17 6.802217 8.458028 HP -0.00643 0.000919 -6.99556 1.32E-07 -0.00831 -0.00455Related Questions
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