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Assignment You have been hired to conduct business research for the purpose of identifying ways to improve fuel efficiency without disturbing consumer preference. Use the data presented to create a multiple regression model which explains the impact of the variables you selected on City and Highway fuel economy. You will have two separate drop boxes for this assignment: one for your calculations (Excel) and one for your written report. Both dropboxes will be located in Week 7 and both files will be due before the course ends on March 1. (1) Make a frequency distributions and/or histograms for CityMPG and HwyMPG. Describe the distributions. (2) Create and discuss the descriptive statistics for all varables. Use tables to present measures of central tendencies and measures of dispersion for continous variables. Use tables, graphs, and charts to present frequencies and descriptives for nominal data. Be sure to identify, report, and recommend a treatment for any outliers. (3) Detimine if there is a statisticsally significant difference in CityMPG based on vehicle body style. Be sure to use Tukey's test to determine if all styles are different. Do the same for HwyMPG. Are the results the same for City and Hwy? (4) Create a scatter plot for X = Weight and Y = CityMPG. What does it suggest? Fit a simple regression on the scatter plot. Interpret the slope and fit. (5) Estimate a multiple regression model using CityMPG as the response variable (dependent variable) and several numerical or binary predictors of your choice. Caution: If you use binary predictors, be careful to omit one of the binary predictors in each group (body style, drive type, transmission type) to avoid perfect multicollinearity. (6) Did your multiple regression model offer a substantially better fit than the simple regression in step (4)? Data Automobile Specifications (n = 73, m = 27) Note: See variable definitions below Body Style (omit one) Drive Type (omit one) Transmission Type (omit one) Obs Model Doors Style Engine Cylinders CityMPG HwyMPG EngineSize HP Length Width Height Weight Drive Transmission TransType NumGears Coupe? Hatchback? Sedan? SUV? FWD? RWD? AWD? Automatic? Manual? CVT? 1 Acura TL 4 Sedan V6 6 20 29 3500 220 109.3 74.0 57.2 3968 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 2 Audi A5 2 Coupe L4 4 22 32 1984 220 108.3 73.0 54.0 3583 A M-6 M 6 1 0 0 0 0 0 1 0 1 0 3 BMW 4 Series 428i 2 Coupe L4 4 22 35 1997 240 182.6 71.9 54.2 3470 R A-8 A 8 1 0 0 0 0 1 0 1 0 0 4 BMW X1 sDrive28i 4 SUV L4 4 23 34 1997 240 176.5 70.8 60.8 3527 R A-8 A 8 0 0 0 1 0 1 0 1 0 0 5 Buice LaCrosse 4 Sedan V6 6 18 28 3600 304 196.9 73.1 59.2 3990 A A-6 A 6 0 0 1 0 0 0 1 1 0 0 6 Buick Enclave 4 SUV V6 6 17 24 3600 288 201.9 79.0 70.3 4724 F A-6 A 6 0 0 0 1 1 0 0 1 0 0 7 Buick Regal 4 Sedan L4 4 21 30 2000 259 190.2 73.1 58.4 3692 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 8 Cadillac ATS 4 Sedan L4 4 22 33 2500 202 182.8 71.1 55.9 3315 R A-6 A 6 0 0 1 0 0 1 0 1 0 0 9 Cadillac CTS 4 Sedan L4 4 20 30 2000 272 195.5 72.2 57.2 3616 R A-6 A 6 0 0 1 0 0 1 0 1 0 0 10 Cadillac Escalade 4 SUV V8 8 14 18 6200 403 202.5 79.0 75.9 5527 R A-6 A 6 0 0 0 1 0 1 0 1 0 0 11 Chevrolet Camaro 1SS 2 Coupe V8 8 16 24 3600 426 190.6 75.5 54.2 3719 R M-6 M 6 1 0 0 0 0 1 0 0 1 0 12 Chevrolet Cruze LS 4 Sedan L4 4 26 38 1400 138 181.0 70.7 58.1 3097 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 13 Chevrolet Impala LTZ 4 Sedan V6 6 19 29 3600 305 201.3 73.0 58.9 3800 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 14 Chevrolet Malibu 2LT 4 Sedan L4 4 25 36 2500 196 191.5 73.0 57.6 3532 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 15 Chevrolet Spark LS 4 Hatchback L4 4 31 39 1200 84 144.7 61.0 62.9 2269 F M-5 M 5 0 1 0 0 1 0 0 0 1 0 16 Chevrolet Suburban LTZ 4 SUV V8 8 15 21 5300 320 224.0 80.5 74.4 5674 R A-6 A 6 0 0 0 1 0 1 0 1 0 0 17 Chrysler 200 Touring LX 4 Sedan L4 4 20 31 2400 173 191.7 72.5 54.9 3402 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 18 Chrysler 300 S 4 Sedan V6 6 19 31 3600 300 198.6 75.0 58.7 4029 R A-8 A 8 0 0 1 0 0 1 0 1 0 0 19 Dodge Charger SXT 4 Sedan V6 6 19 31 3600 292 199.9 75.0 58.4 3996 R A-8 A 8 0 0 1 0 0 1 0 1 0 0 20 Dodge Dart Limited 4 Sedan L4 4 23 35 2400 184 183.9 72.0 57.7 3242 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 21 Fiat 500 Sport 2 Hatchback L4 4 31 40 1400 135 139.6 64.1 59.8 2434 F M-5 M 5 0 1 0 0 1 0 0 0 1 0 22 Ford Fiesta S 4 Hatchback L4 4 29 39 1600 120 159.7 67.8 58.1 2575 F A-6 A 6 0 1 0 0 1 0 0 1 0 0 23 Ford Focus SE 4 Sedan L4 4 27 37 2000 160 178.5 71.8 57.7 2960 F M-5 M 5 0 0 1 0 1 0 0 0 1 0 24 Ford Mustang GT 2 Coupe V8 8 15 26 5000 420 188.5 73.9 55.8 3618 R M-6 M 6 1 0 0 0 0 1 0 0 1 0 25 Ford Taurus 4 Sedan V6 6 19 29 3500 288 202.9 76.2 60.7 4054 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 26 Honda Accord LX 4 Sedan L4 4 24 34 2356 185 191.4 72.8 57.7 3192 F M-6 M 6 0 0 1 0 1 0 0 0 1 0 27 Honda CRV LX 4 SUV L4 4 23 31 2354 185 178.3 71.6 64.7 3305 F A-5 A 5 0 0 0 1 1 0 0 1 0 0 28 Hyundai Azera Limited 4 Sedan V6 6 19 29 3300 293 193.3 73.2 57.9 3605 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 29 Hyundai Genesis 5.0 4 Sedan V8 8 15 23 5000 429 196.5 74.4 58.3 4240 R A-8 A 8 0 0 1 0 0 1 0 1 0 0 30 Hyundai Santa Fe GLS 4 SUV V6 6 18 25 3300 290 193.1 74.2 66.9 3933 F A-6 A 6 0 0 0 1 1 0 0 1 0 0 31 Infiniti Q60 4 Coupe V6 6 19 27 3700 330 183.1 71.8 54.8 3633 R A-7 A 7 1 0 0 0 0 1 0 1 0 0 32 Infiniti QX50 4 SUV V6 6 17 25 3700 325 182.3 71.0 61.9 3790 R A-7 A 7 0 0 0 1 0 1 0 1 0 0 33 Jaguar F-Type 2 Coupe V6 6 20 28 3000 340 176.0 75.7 51.5 3477 R A-8 A 8 1 0 0 0 0 1 0 1 0 0 34 Jeep Compass Limited 4 SUV L4 4 21 28 2400 172 175.1 71.4 65.0 3258 F A-6 A 6 0 0 0 1 1 0 0 1 0 0 35 Jeep Grand Cherokee Limited 4 SUV V6 6 17 25 3600 290 189.8 76.5 68.1 4685 R A-8 A 8 0 0 0 1 0 1 0 1 0 0 36 Kia Forte LX 4 Sedan L4 4 25 36 1797 148 179.5 70.1 56.5 2776 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 37 Kia Soul 4 Hatchback L4 4 24 30 1600 138 163.0 70.9 63.0 2615 F M-6 M 6 0 1 0 0 1 0 0 0 1 0 38 Kia Sportage LX 4 SUV L4 4 21 30 2359 176 174.8 73.0 64.4 3186 F A-6 A 6 0 0 0 1 1 0 0 1 0 0 39 Land Rover Range Rover Sport 4 SUV V8 8 13 19 5000 510 196.8 81.6 72.3 5137 A A-8 A 8 0 0 0 1 0 0 1 1 0 0 40 Lexus IS 250 2 Sedan V6 6 21 30 2500 204 183.7 71.3 56.3 3461 R A-6 A 6 0 0 1 0 0 1 0 1 0 0 41 Lexus LS 460 4 Sedan V8 8 16 24 4600 386 200.0 73.8 58.1 4233 R A-8 A 8 0 0 1 0 0 1 0 1 0 0 42 Lexus RX 350 4 SUV V6 6 18 25 3500 270 187.8 74.2 66.7 4178 F A-6 A 6 0 0 0 1 1 0 0 1 0 0 43 Lincoln MKT 4 SUV V6 6 17 25 3700 303 207.6 76.0 67.4 4702 F A-6 A 6 0 0 0 1 1 0 0 1 0 0 44 Lincoln MKZ 4 Sedan L4 4 22 33 2000 240 194.1 73.4 58.2 3713 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 45 Lincoln Navigator 4 SUV V8 8 14 20 5400 310 208.4 78.8 78.3 5794 R A-6 A 6 0 0 0 1 0 1 0 1 0 0 46 Mazda 2 4 Hatchback L4 4 28 34 1500 100 155.5 66.7 58.1 2306 F M-5 M 5 0 1 0 0 1 0 0 0 1 0 47 Mazda CX-5 Sport 4 SUV L4 4 26 32 2000 155 179.3 72.4 67.3 3194 F A-6 A 6 0 0 0 1 1 0 0 1 0 0 48 Mercedes-Benz C-250 4 Sedan L4 4 22 31 1800 201 180.8 69.7 56.9 3428 R A-7 A 7 0 0 1 0 0 1 0 1 0 0 49 Mercedes-Benz CL600 2 Coupe V12 2 12 18 5500 510 200.6 84.2 55.8 4894 R A-5 A 5 1 0 0 0 0 1 0 1 0 0 50 Mercedes-Benz ML350 4 SUV V6 6 17 22 3500 302 189.1 84.3 70.7 4751 R A-7 A 7 0 0 0 1 0 1 0 1 0 0 51 Mini-Cooper 2 Hatchback L4 4 29 37 1600 121 146.6 66.3 55.4 2605 F M-6 M 6 0 1 0 0 1 0 0 0 1 0 52 Mitsubishi Outlander Sport SE 4 SUV L4 4 25 31 2400 166 183.3 70.9 66.1 3296 F CVT C 0 0 0 1 1 0 0 0 0 1 53 Nissan Armada SV 4 SUV V8 8 13 19 5600 317 207.7 79.3 77.2 5267 R A-5 A 5 0 0 0 1 0 1 0 1 0 0 54 Nissan Cube S 4 Hatchback L4 4 25 30 1800 127 156.7 66.7 65.0 2789 F M-6 M 6 0 1 0 0 1 0 0 0 1 0 55 Nissan Maxima SV 4 Sedan V6 6 19 26 3500 290 190.6 73.2 57.8 3570 F CVT C 0 0 1 0 1 0 0 0 0 1 56 Nissan Murano SV 4 SUV V6 6 18 24 3500 260 189.9 74.1 67.0 4011 F CVT C 0 0 0 1 1 0 0 0 0 1 57 Nissan Versa S 4 Sedan L4 4 27 36 1600 109 175.4 66.7 59.6 2363 F M-5 M 5 0 0 1 0 1 0 0 0 1 0 58 Porsche Cayenne 4 SUV V6 6 15 22 3600 300 190.8 76.3 67.4 4398 A M-6 M 6 0 0 0 1 0 0 1 0 1 0 59 Scion FR-S 2 Coupe L4 4 25 34 2000 200 166.7 69.9 50.6 2806 R A-6 A 6 1 0 0 0 0 1 0 1 0 0 60 Scion iQ 2 Hatchback L4 4 36 37 1329 94 120.1 66.1 59.1 2127 F CVT C 0 1 0 0 1 0 0 0 0 1 61 Scion XD 4 SUV L4 4 27 33 1798 128 154.7 67.9 59.4 2665 F A-4 A 4 0 0 0 1 1 0 0 1 0 0 62 Suburu Forester 2.5i Limited 4 SUV L4 4 24 32 2500 170 180.9 70.7 68.2 3419 A CVT C 0 0 0 1 0 0 1 0 0 1 63 Suburu Legacy 2.5i Limited 4 Sedan L4 4 24 32 2500 173 187.2 71.7 59.3 3427 A CVT C 0 0 1 0 0 0 1 0 0 1 64 Toyota Camry XLE 4 Sedan L4 4 25 35 2500 178 189.2 71.7 57.9 3280 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 65 Toyota Land Cruiser 4 SUV V8 8 13 18 5700 381 194.9 77.6 74.0 5765 A A-6 A 6 0 0 0 1 0 0 1 1 0 0 66 Toyota RAV4 XLE 4 SUV L4 4 24 31 2500 176 179.9 72.6 67.1 3465 F A-6 A 6 0 0 0 1 1 0 0 1 0 0 67 Toyota Yaris 3 Hatchback L4 4 30 37 1500 106 153.5 66.7 59.4 2295 F M-5 M 5 0 1 0 0 1 0 0 0 1 0 68 Volkswagen Beetle 2.5L 2 Coupe L4 4 22 29 2500 170 168.4 71.2 58.6 3038 F A-6 A 6 1 0 0 0 1 0 0 1 0 0 69 Volkswagen Jetta SE 4 Sedan L4 4 25 36 1800 170 182.2 70.0 57.2 3070 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 70 Volkswagen Toureg V6 Sport 4 SUV V6 6 17 23 3600 280 188.8 76.4 68.2 4711 A A-8 A 8 0 0 0 1 0 0 1 1 0 0 71 Volkswagen Passat SE 4 Sedan L4 4 24 34 1800 170 191.6 72.2 58.5 3230 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 72 Volvo S60 T5 4 Sedan L5 5 21 30 2500 250 182.2 73.4 58.4 3528 F A-6 A 6 0 0 1 0 1 0 0 1 0 0 73 Volvo XC90 4 SUV L6 6 16 25 3200 240 189.3 76.2 70.2 4667 F A-6 A 6 0 0 0 1 1 0 0 1 0 0 unusual unusual does not apply Step 1: Create and report descriptive statistics for all nominal variables using charts, graphs, and tables. Step 2: Create Source: Vehicles are a random sample of 2014 vehicles sold in the U.S.. Data are from manufacturer web sites. All vehicles are gas or flex-fuel (no hybrids or electrics) . This information is intended only as a training data set for statistics students, and should not be viewed as a guide to specific vehicle performance or purchase decisions. Variable Definitions Doors = number of doors Style = body style (coupe, hatchback, sedan, SUV) Engine = type of engine (L4, L5, L6, V6, V8) Cylinders = number of engine cylinders CityMPG = estimated EPA city miles per gallon HwyMPG = estimated EPA highway miles per gallon EngineSize = engine displacement (cc) HP = engine horsepower Length = length of vehicle (inches) Width = width of vehicle (inches) Height = height of vehicle (inches) Weight = curb weight of vehicle (pounds) Drive = drive type (front wheel, rear wheel, all wheel) Transmission = transmission type and gears (e.g., A6) TransType = automatic (A), manual (M), continuously variable(C) NumGears = number of gears Coupe? = 1 if vehicle is a couple body style, 0 otherwise Hatchback? = 1 if vehicle is a hatchback body style, 0 otherwise Sedan? = 1 if vehicle is a sedan body style, 0 otherwise SUV? = 1 if vehicle is an SUV body style, 0 otherwise FWD? = 1 if vehicle is front wheel drive, 0 otherwise RWD? = 1 if vehicle is rear wheel drive, 0 otherwise AWD? = 1 if vehicle is all-wheel drive, 0 otherwise Automatic? = 1 if automatic transmission, 0 otherwise Manual? = 1 if manual transmission, 0 otherwise CVT? = 1 if continuously variable transmission, 0 otherwise Exercise Suggestions: (1) Make a frequency distributions and/or histograms for CityMPG and HwyMPG. Describe the distributions. (2) Create and discuss the descriptive statistics for all varables. Use tables to present measures of central tendencies and measures of dispersion for continous variables. Use tables, graphs, and charts to present frequencies and descriptives for nominal data. Be sure to identify, report, and recommend a treatment for any outliers. (3) Detimine if there is a statisticsally significant difference in CityMPG based on vehicle body style. Be sure to use Tukey's test to determine if all styles are different. Do the same for HwyMPG. Are the results the same for City and Hwy? (4) Create a scatter plot for X = Weight and Y = CityMPG. What does it suggest? Fit a simple regression on the scatter plot. Interpret the slope and fit. (5) Estimate a multiple regression model using CityMPG as the response variable (dependent variable) and several numerical or binary predictors of your choice. Caution: If you use binary predictors, be careful to omit one of the binary predictors in each group (body style, drive type, transmission type) to avoid perfect multicollinearity. (6) Did your multiple regression model offer a substantially better fit than the simple regression in step (4)? Extra Sheet LearningStatsCopyright © 2019byThe McGraw-Hill CompaniesThis spreadsheet is intended solely for educational purposes by licensed users of Connect

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