/* libname q 'Q:\\Courses\\ECN410\\CoxDornelles'; */ /* use the data set q.cox_p1d1 which consists of: DATA ON CABLE SYSTEMS IN THE TOP 40 TELEVISION MARKETS sub = The number of subscribers of each system (in thousands) home = The number of homes passed by each system inst = Installation fee in dollars svc = Monthly service charge of each system (Range 5.6 - 10) tv = The number of television signals carried by each cable system age = The age of each system in years air = The number of television signals received income = Per capita income for each television market with cable, in dollars */ /* Your task is to develop a model to predict the the number of subscribers for a new market with the following characteristics home = 50 inst = 17.5 svc = 6, 7, 8, and 9, you want to assess the impact of charging different monthly rates tv = 12 age = 1 (this is a new market and the system will be new) air = 4 (currently people in the market have access to four stations) income = 9500 first fit a benchmark model with all of the independent variables then report any issues that you find and make any changes to your model that you think are appropriate such as transforming variables. Be sure to report summary statistics as well as appropriate regression output and a justification for any changes that you make. */ /* proc means data=q.cox_p1d1; run; proc print data=q.cox_p1d1; run; */ DATA P1D1; *** data for the project***; INPUT id $ SUB HOME INST SVC TV AGE AIR INCOME; drop id; CARDS; 1 105.000 350.000 14.95 10.00 16 11.83 13 9839 2 90.000 255.631 15.00 7.50 15 11.42 11 10606 3 14.000 31.000 15.00 7.00 11 7.33 9 10455 4 11.700 34.840 10.00 7.00 22 6.92 10 8958 5 46.000 153.434 25.00 10.00 20 26.00 12 11741 6 11.217 26.621 15.00 7.66 18 8.83 8 9378 7 12.000 18.000 15.00 7.50 12 13.08 8 10433 8 6.428 9.324 15.00 7.00 17 5.58 7 10167 9 20.100 32.000 10.00 5.60 10 12.42 8 9218 10 8.500 28.000 15.00 6.50 6 4.92 6 10519 11 1.600 8.000 17.50 7.50 8 4.08 6 10025 12 1.100 5.000 15.00 8.95 9 4.25 9 9714 13 4.355 15.204 10.00 7.00 7 10.67 7 9294 14 78.910 97.889 24.95 9.49 12 17.58 7 9784 15 19.600 93.000 20.00 7.50 9 8.08 7 8173 16 1.000 3.000 9.95 10.00 13 0.17 6 8967 17 1.650 2.600 25.00 7.55 6 13.25 5 10133 18 13.400 18.284 15.50 6.30 11 12.67 5 9361 19 18.708 55.000 15.00 7.00 16 5.25 6 9085 20 1.352 1.700 20.00 5.60 6 15.00 6 10067 21 170.000 270.000 15.00 8.75 15 17.00 5 8908 22 15.388 46.540 15.00 8.73 9 6.83 6 9632 23 6.555 20.417 5.95 5.95 10 5.67 6 8995 24 40.000 120.000 25.00 6.50 10 7.00 5 7787 25 19.900 46.390 15.00 7.50 9 11.25 7 8890 26 2.450 14.500 9.95 6.25 6 2.92 4 8041 27 3.762 9.500 20.00 6.50 6 2.17 5 8605 28 24.882 81.980 18.00 7.50 8 7.08 4 8639 29 21.187 39.700 20.00 6.00 9 12.17 4 8781 30 3.487 4.113 10.00 6.85 11 13.08 4 8551 31 3.000 8.000 10.00 7.95 9 0.17 6 9306 32 42.100 99.750 9.95 5.73 8 7.67 5 8346 33 20.350 33.379 15.00 7.50 8 10.33 4 8803 34 23.150 35.500 17.50 6.50 8 12.25 5 8942 35 9.866 34.775 15.00 8.25 11 2.00 4 8591 36 42.608 64.840 10.00 6.00 11 13.08 6 9163 37 10.371 30.556 20.00 7.50 8 1.00 6 7683 38 5.164 16.500 14.95 6.95 8 4.00 5 7924 39 31.150 70.515 9.95 7.00 10 4.67 4 8454 40 18.350 42.040 20.00 7.00 6 3.00 4 8429 ; proc means data =P1D1; run