options linesize=80 nodate nonumber; DATA DIALBUS; INPUT NAME $ 1-10 POP AREA DENSITY RIDERS HOURS DEMAND VEHS FARE X Y IND; LHOURS=LOG(HOURS); LRIDERS=LOG(RIDERS+.5); LPOP=LOG(POP);LAREA=LOG(AREA);LDENSITY=LOG(DENSITY); LVEHS=LOG(VEHS);LFARES=LOG(FARE); n=_n_; DATALINES; ANNARBOR-A 100000 13.6 7353 2718 18.5 10.8 22 .25 5.6 3.25 1 ANNARBOR-B 8872 2.3 3857 250 12.0 9.1 3 .35 7.0 3.25 0 BATAVIA,NY 17338 4.3 4032 350 12.0 6.8 2 .60 11.5 0 1 BIRMINGHAM 26170 4.6 5689 186 12.0 3.4 4 .50 6.6 3.25 0 ELCONJONE 60000 17.0 3529 600 12.0 2.9 14 .50 7.4 0 0 FAIRFIELD 40000 7.0 5714 420 12.0 5.0 5 .50 7.0 0 1 FERNDALE 30850 3.9 7910 249 12.0 5.3 2 .50 7.7 3.25 1 GAITHERSBG 25000 6.5 3846 350 13.0 4.1 8 .25 5.0 0 0 HADDONFLDA 44000 10.9 4036 925 24.0 4.6 19 .30 4.9 0 0 HADDONFLDB 24300 6.4 3800 514 24.0 3.3 12 .60 4.6 0 0 HARPERWOOD 21455 2.6 8252 117 8.0 5.6 4 .50 9.6 3.25 0 LAHABRA,CA 47000 7.0 6714 450 12.0 5.4 7 .50 7.9 0 0 LAMESA,CA 45000 7.0 6429 275 12.0 3.3 5 .50 5.6 0 0 LAMIRADA 23000 6.0 5333 360 12.0 5.0 6 .25 8.5 0 1 MT.CLEMENS 20476 3.8 5388 307 11.0 7.3 4 .50 9.1 3.25 1 MTPLEASANT 20504 5.1 4020 227 12.0 3.7 5 .50 5.9 4.10 0 REDFORDTWN 71901 15.8 4551 208 12.0 1.1 4 .60 4.8 3.35 0 ROCHESTERA 70000 12.0 5833 700 16.3 3.6 13 1.00 5.5 0 0 ROCHESTERB 30000 10.0 3000 440 12.0 3.7 7 1.00 5.3 0 0 TOLEDO,OH 26689 3.5 7625 275 15.0 5.2 4 0.01 4.6 0 1 ALMA,MI 9790 4.6 2128 201 15.5 2.8 3 .50 5.4 3.37 0 ALPENA,MI 19805 10.4 1904 314 14.0 2.2 5 .50 6.2 3.75 1 BELDING,MI 5321 4.7 1132 95 15.0 1.3 2 .50 5.9 3.39 0 BENTONHARB 56828 51.6 1101 679 12.0 1.1 15 .60 6.6 3.80 1 BIGRAPIDS 11995 5.1 2352 224 12.0 3.7 4 .50 6.9 3.35 0 CADILLAC 10490 6.1 1720 277 12.0 3.8 4 .50 6.9 0 1 DOWAGIAC 7883 4.1 1923 67 10.0 1.6 2 .50 5.7 3.25 0 GLADWIN 3025 2.4 1260 83 8.0 4.3 2 .50 9.8 4.05 0 GRANDHAVEN 17074 7.5 2227 245 12.0 2.7 4 .50 6.8 3.55 1 HILLSDALE 7728 4.3 1797 148 12.0 2.9 3 .50 6.5 3.50 0 HOLLAND 27137 14.2 1911 266 12.0 1.6 6 .50 6.5 3.85 0 HOUGHTON 12287 4.1 2997 270 12.0 5.5 4 .50 7.4 0 1 ISABELLACO 24090 568.0 42 56 10.5 0.0 3 .50 1.6 4.10 0 LUDUNGTON 9521 4.3 2214 236 12.0 4.6 4 .50 7.8 4.70 1 MANISTEECO 18404 408.0 45 251 12.0 0.0 5 .50 6.9 3.25 1 MARSHALL 7253 4.6 1577 150 12.0 2.7 3 .50 6.3 3.50 0 MERCED,CA 28500 10.0 2850 370 10.0 3.7 5 .25 8.1 0 1 MIDLAND 35176 24.9 1413 464 16.8 1.1 10 .50 5.4 5.22 0 NILES 12988 5.2 2498 260 12.0 4.2 5 .50 5.9 3.50 0 ROSCOMMONC 9892 251.0 19 63 12.0 0.0 3 .50 1.9 0 0 SAULTSTMRE 15136 15.7 964 341 14.5 1.5 6 .50 6.2 3.13 1 TRAVERSECY 26321 17.8 1479 222 12.0 1.0 6 .50 6.4 3.45 0 TURLOCK,CA 18000 10.0 1800 200 10.0 2.0 3 .50 6.6 0 1 MERRILL,WS 9500 5.5 1700 228 11.5 3.6 3 .25 9.6 0 1 XENIA,OHIO 27600 9.0 3070 900 12.0 8.3 4 .10 8.7 0 1 TRENTON 24127 7.2 3351 199 12.0 2.3 6 .60 6.2 3.25 0 BAYRIDGE 14000 4.0 3500 600 20.0 7.5 6 .25 9.7 0 1 BUFFALO 53860 3.0 18000 300 17.0 5.9 10 0.01 8.9 0 0 COLUMBIA 18000 28.0 643 310 14.5 7.4 9 .25 6.9 0 0 COLUMBUS 29103 2.5 11600 369 15.2 10.6 4 .20 8.8 0 1 DETROIT 102711 9.5 10800 400 16.0 2.6 11 0.01 6.3 3.25 0 KINGSTON 25000 5.0 5000 140 5.0 5.6 2 .35 11.7 0 1 REGINA 32000 5.0 6400 3400 18.7 25.0 12 .35 20.0 0 1 STRATFORD 35000 7.0 5000 200 4.0 7.1 4 .35 12.5 0 1 ; proc nlin data=dialbus nohalve; parms b0=1 b1=.16 b2=-.28 b3=.75 b4=.94 b5=.12 b6=.93 ; model lriders=b0+b1*lpop+b2*larea+b3*lhours+b4*lvehs+b5*lfares+b6*ind; w=exp(model.lriders); _weight_=w; output out=a p=p; run; data b; set a;w=exp(p); Proc reg; model lriders=lpop larea lvehs lfares lhours ind / influence; weight w; run; data c; set dialbus; if (n=1 or n=45 or n=53) then delete; run; proc nlin data=c nohalve; parms b0=1 b1=.16 b2=-.28 b3=.75 b4=.94 b5=.12 b6=.93 ; model lriders=b0+b1*lpop+b2*larea+b3*lhours+b4*lvehs+b5*lfares+b6*ind; w=exp(model.lriders); _weight_=w; output out=a2 p=p2; run; data d; set a2; w=exp(p2); Proc reg; model lriders=lpop larea lvehs lfares lhours ind / influence; weight w; output out= a3 student=s2; proc univariate plot normal; var s2; run;