SAS programming PLEASE HELP

profilerdoos

The car data are observations from cars selling on North American market. Five variables were collected for each car: Weight, Disp. (the engine displacement in liters), Mileage, Fuel and Type.

 

a) Fit the following regression model: Mileage = 0 + 1 weight + 2 Disp: + 3 F uel + 4 T ype + error [Hint: Use PROC GLM rather than PROC REG and use the class statement in GLM (Think WHY?)].

 

b) Create a new data set which does not contain the "Type" variable. Find the best regression model for this new data set. [Hint: Now we can use PROC REG. (Again why?)] If you are interested, you can add the option 'SELECTION'. For details, make reference to the book on page 161. Following is the recommended code for this option. MODEL Mileage = Weight Disp Fuel/SELECTION = backward; /*forward, stepwise*/ Please show how to fit the regression line like please put the code that I can use in Sas to import the data and then answer both questions A and B.

DATA!!!

 

Eagle Summit 4 2560 97 33 3.030303 Small

Ford Escort 4 2345 114 33 3.030303 Small

Ford Festiva 4 1845 81 37 2.702703 Small

Honda Civic 4 2260 91 32 3.125000 Small

Mazda Protege 4 2440 113 32 3.125000 Small

Mercury Tracer 4 2285 97 26 3.846154 Small

Nissan Sentra 4 2275 97 33 3.030303 Small

Pontiac LeMans 4 2350 98 28 3.571429 Small

Subaru Loyale 4 2295 109 25 4.000000 Small

Subaru Justy 3 1900 73 34 2.941176 Small

Toyota Corolla 4 2390 97 29 3.448276 Small

Toyota Tercel 4 2075 89 35 2.857143 Small

Volkswagen Jetta 4 2330 109 26 3.846154 Small

Chevrolet Camaro V8 3320 305 20 5.000000 Sporty

Dodge Daytona 2885 153 27 3.703704 Sporty

Ford Mustang V8 3310 302 19 5.263158 Sporty

Ford Probe 2695 133 30 3.333333 Sporty

Honda Civic CRX Si 4 2170 97 33 3.030303 Sporty

Honda Prelude Si 4WS 4 2710 125 27 3.703704 Sporty

Nissan 240SX 4 2775 146 24 4.166667 Sporty

Plymouth Laser 2840 107 26 3.846154 Sporty

Subaru XT 4 2485 109 28 3.571429 Sporty

Audi 80 4 2670 121 27 3.703704 Compact

Buick Skylark 4 2640 151 23 4.347826 Compact

Chevrolet Beretta 4 2655 133 26 3.846154 Compact

Chrysler Le Baron V6 3065 181 25 4.000000 Compact

Ford Tempo 4 2750 141 24 4.166667 Compact

Honda Accord 4 2920 132 26 3.846154 Compact

Mazda 626 4 2780 133 24 4.166667 Compact

Mitsubishi Galant 4 2745 122 25 4.000000 Compact

Mitsubishi Sigma V6 3110 181 21 4.761905 Compact

Nissan Stanza 4 2920 146 21 4.761905 Compact

Oldsmobile Calais 4 2645 151 23 4.347826 Compact

Peugeot 405 4 2575 116 24 4.166667 Compact

Subaru Legacy 4 2935 135 23 4.347826 Compact

Toyota Camry 4 2920 122 27 3.703704 Compact

Volvo 240 4 2985 141 23 4.347826 Compact

Acura Legend V6 3265 163 20 5.000000 Medium

Buick Century 4 2880 151 21 4.761905 Medium

Chrysler Le Baron Coupe 2975 153 22 4.545455 Medium

Chrysler New Yorker V6 3450 202 22 4.545455 Medium

Eagle Premier V6 3145 180 22 4.545455 Medium

Ford Taurus V6 3190 182 22 4.545455 Medium

Ford Thunderbird V6 3610 232 23 4.347826 Medium

Hyundai Sonata 4 2885 143 23 4.347826 Medium

Mazda 929 V6 3480 180 21 4.761905 Medium

Nissan Maxima V6 3200 180 22 4.545455 Medium

Oldsmobile Cutlass Ciera 4 2765 151 21 4.761905 Medium

Oldsmobile Cutlass Supreme V6 3220 189 21 4.761905 Medium

Toyota Cressida 6 3480 180 23 4.347826 Medium

Buick Le Sabre V6 3325 231 23 4.347826 Large

Chevrolet Caprice V8 3855 305 18 5.555556 Large

Ford LTD Crown Victoria V8 3850 302 20 5.000000 Large

Chevrolet Lumina APV V6 3195 151 18 5.555556 Van

Dodge Grand Caravan V6 3735 202 18 5.555556 Van

Ford Aerostar V6 3665 182 18 5.555556 Van

Mazda MPV V6 3735 181 19 5.263158 Van

Mitsubishi Wagon 4 3415 143 20 5.000000 Van

Nissan Axxess 4 3185 146 20 5.000000 Van

Nissan Van 4 3690 146 19 5.263158 Van

    • 11 years ago
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