This table presents information on the performance of 25 different vehicles (source: MotorTrend) Legend: y: miles/gallon
Posted: Wed Jul 06, 2022 12:09 pm
This table presents information on the performanceof 25 different vehicles (source:MotorTrend)
Legend:y: miles/gallon (MPG)x1: Displacement (cubic inches)x2: Horsepower (foot-pounds)x3: torque (foot-pounds)x4: compression ratiox5: rear axle ratiox6: carburetor (barrels)x7: number of baud ratesx8: overall length (inches)x9: width (inches)x10: weight (pounds)x11: Transmission type (A - automatic, M - manual)
A). Estimate the multiple linearregression modelrelating MPG (miles/gallon (MPG)) to theengine displacement (x1) and the number of carburetor barrels(x6).
B). Estimate the σ
.C). Use the model developedin A). to predict the performance of thevehicle when x1 = 300 and x6 = 2.
D). Test the significance of the regressionusing an α = 0.05. What conclusion can do?
E). Find the tstatistic for both regressors. Using an α = 0.05,what conclusion can you reach? Do both regressors contribute to themodel?
F). Estimate a new regression for the datausing the variables x1, x2, x6, and x11. Do you think thisregression is better atpredicting MPG than the developedin A).? Justify youranswer
Vehículo Apollo Nova Monarch Duster y 18.90 20.00 18.25 20.07 Jenson Conv. 11.2 Skyhawk 22.12 Scirocco 34.70 Corolla SR-5 30.40 16.50 Camaro Datsun B210 Capri II Pacer Granada Eldorado Imperial Nova LN Starfire Cordoba Trans Am Corolla E-5 Mark IV Celica GT Charger SE Cougar Corvette 36.50 21.50 19.70 17.80 14.39 14.89 17.80 23.54 21.47 16.59 31.90 13.27 23.90 19.73 13.90 16.50 x1 350 250 351 225 440 231 89.7 96.9 350 85.3 171 258 302 500 440 350 231 360 400 96.9 460 133.6 318 351 350 x2 165 105 143 95 215 110 70 75 155 80 109 110 129 190 215 155 110 180 185 75 223 96 140 148 165 x3 260 185 255 170 330 175 81 83 250 83 146 195 220 360 330 250 175 290 ΝΑ 83 366 120 255 243 255 x4 8.0:1 8.25:1 8.0:1 8.4:1 8.2:1 8.0:1 8.2:1 9.0:1 8.5:1 8.5:1 8.2:1 8.01 8.0:1 8.5:1 8.2:1 8.5:1 8.0:1 8.4:1 7.6:1 9.0:1 8.0:1 8.4:1 8.5:1 8.0:1 8.5:1 x5 2.56:1 2.73:1 3.00:1 2.76:1 2.88:1 2.56:1 3.90:1 4.30:1 3.08:1 3.89:1 3.22:1 3.08:1 3.0:1 2.73:1 2.71:1 3.08:1 2.56:1 2.45:1 3.08:1 4.30:1 3.00:1 3.91:1 2.71:1 3.25:1 2.73:1 x6 4 1 2 1 4 2 2 2 4 2 2 1 2 4 4 4 2 2 4 2 4 2 2 2 4 x7 3 3 3 3 3 3 4 5 3 4 4 3 3 3 3 3 3 3 3 5 3 5 3 3 3 x8 200.3 196.7 199.9 194.1 184.5 179.3 155.7 165.2 195.4 160.6 170.4 171.5 199.9 224.1 231.0 196.7 179.3 214.2 196 165.2 228 171.5 215.3 215.5 185.2 x9 69.9 72.2 74.0 71.8 69 65.4 64 65 74.4 62.2 66.9 77 74 79.8 79.7 72.2 65.4 76.3 73 61.8 79.8 63.4 76.3 78.5 69 x10 3910 3510 3890 3365 4215 3020 1905 2320 3885 2009 2655 3375 3890 5290 5185 3910 3050 4250 3850 2275 5430 2535 4370 4540 3660 x11 A A A M A A M M A M M A A A A A A A A M A M A A A
- This Table Presents Information On The Performance Of 25 Different Vehicles Source Motortrend Legend Y Miles Gallon 1 (96.68 KiB) Viewed 13 times
A). Estimate the multiple linearregression modelrelating MPG (miles/gallon (MPG)) to theengine displacement (x1) and the number of carburetor barrels(x6).
B). Estimate the σ
.C). Use the model developedin A). to predict the performance of thevehicle when x1 = 300 and x6 = 2.
D). Test the significance of the regressionusing an α = 0.05. What conclusion can do?
E). Find the tstatistic for both regressors. Using an α = 0.05,what conclusion can you reach? Do both regressors contribute to themodel?
F). Estimate a new regression for the datausing the variables x1, x2, x6, and x11. Do you think thisregression is better atpredicting MPG than the developedin A).? Justify youranswer
Vehículo Apollo Nova Monarch Duster y 18.90 20.00 18.25 20.07 Jenson Conv. 11.2 Skyhawk 22.12 Scirocco 34.70 Corolla SR-5 30.40 16.50 Camaro Datsun B210 Capri II Pacer Granada Eldorado Imperial Nova LN Starfire Cordoba Trans Am Corolla E-5 Mark IV Celica GT Charger SE Cougar Corvette 36.50 21.50 19.70 17.80 14.39 14.89 17.80 23.54 21.47 16.59 31.90 13.27 23.90 19.73 13.90 16.50 x1 350 250 351 225 440 231 89.7 96.9 350 85.3 171 258 302 500 440 350 231 360 400 96.9 460 133.6 318 351 350 x2 165 105 143 95 215 110 70 75 155 80 109 110 129 190 215 155 110 180 185 75 223 96 140 148 165 x3 260 185 255 170 330 175 81 83 250 83 146 195 220 360 330 250 175 290 ΝΑ 83 366 120 255 243 255 x4 8.0:1 8.25:1 8.0:1 8.4:1 8.2:1 8.0:1 8.2:1 9.0:1 8.5:1 8.5:1 8.2:1 8.01 8.0:1 8.5:1 8.2:1 8.5:1 8.0:1 8.4:1 7.6:1 9.0:1 8.0:1 8.4:1 8.5:1 8.0:1 8.5:1 x5 2.56:1 2.73:1 3.00:1 2.76:1 2.88:1 2.56:1 3.90:1 4.30:1 3.08:1 3.89:1 3.22:1 3.08:1 3.0:1 2.73:1 2.71:1 3.08:1 2.56:1 2.45:1 3.08:1 4.30:1 3.00:1 3.91:1 2.71:1 3.25:1 2.73:1 x6 4 1 2 1 4 2 2 2 4 2 2 1 2 4 4 4 2 2 4 2 4 2 2 2 4 x7 3 3 3 3 3 3 4 5 3 4 4 3 3 3 3 3 3 3 3 5 3 5 3 3 3 x8 200.3 196.7 199.9 194.1 184.5 179.3 155.7 165.2 195.4 160.6 170.4 171.5 199.9 224.1 231.0 196.7 179.3 214.2 196 165.2 228 171.5 215.3 215.5 185.2 x9 69.9 72.2 74.0 71.8 69 65.4 64 65 74.4 62.2 66.9 77 74 79.8 79.7 72.2 65.4 76.3 73 61.8 79.8 63.4 76.3 78.5 69 x10 3910 3510 3890 3365 4215 3020 1905 2320 3885 2009 2655 3375 3890 5290 5185 3910 3050 4250 3850 2275 5430 2535 4370 4540 3660 x11 A A A M A A M M A M M A A A A A A A A M A M A A A