/* Sample SAS code and data for problem 2.44 */

DATA womenpow;

INPUT name $ age company $ postitle $;

cards;

Fiorina         45 Hewlett-Packard         CEO   
Miller          46 Citigroup               CFO   
Meekr           40 MorganStanley           Dir   
Lazarus         52 Ogilvy&Mather           CEO   
Whitman         43 eBay                    CEO   
Hopkins         44 Boeing                  CFO   
Scardino        52 Pearson                 CEO   
Stewart         58 MarthaStewartLiving     CEO   
Peretsma        45 Allen&Co.               EVP   
Russo           47 LucentTechnologies      EVP   
Dunn            46 BarclaysGlobalInvestors Chrmn 
Cohen           47 GoldmanSachs            Dir   
Livermor        41 Hewlett-Packard         CEO   
Jung            41 AvonProducts            COO   
Lansing         55 ParamountPictures       Chrmn 
Katen           50 Pfizer                  EVP   
Nelson          60 CarlsonCos.             CEO   
McGrath         47 MTV&M2                  Pres  
Juliber         50 Colgate-Palmolive       COO   
Laybourn        52 OxygenMedia             CEO   
Estrin          44 CiscoSystems            SrVP  
Black           55 HearstMagazines         Pres  
Sandford        46 IBM                     GM    
Moore           49 TimeInc.                Pres  
Barad           48 Mattel                  CEO   
Winfrey         45 HarpoEntertainment      Chrmn 
Lewent          50 Merck                   SrVP  
Covey           36 Amazon.com              COO   
Mark            45 Azurix                  CEO   
Willingh        43 Microsoft               VP    
Dubion          46 ChaseManhattan          EVP   
Woertz          46 Chevron                 Pres  
Fitt            46 GoldmanSachs            Dir   
Fudge           48 KraftFoods              EVP   
Ticknor         52 Hewlett-Packard         CEO   
Lepore          45 CharlesSchwab           CIO   
Rivet           51 UnitedHealthcare        CEO   
Gorelick        49 FannieMae               VChrm 
Brandt          48 AmericaOnline           Pres  
Macaskil        51 OppenheimerFunds        CEO   
Jackson         48 BananaRepublic          CEO   
Trudell         46 GeneralMotors           VP    
DiSesa          53 McCann-Erickson         Chrmn 
Wachner         53 Warnaco                 Chrmn 
Moore           45 RainwaterInc.           Pres  
Sandler         68 GoldenWest              CEO   
Anthony         42 SonyMusic               EVP   
Gadlesh         48 Bain&Co.                Chrmn 
Beers           64 J.WalterThompson        Chrma 
Johnson         37 FidelityInvestments     VP    


;

title 'Problem 2.44: Powerful Women Data';

proc insight;
open womenpow;
dist age;
run;

/* Another method of getting summary statistics: */

proc univariate data=womenpow;
var age;
run;