% analcatdata A collection of data sets used in the book "Analyzing Categorical Data," % by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission % consists of a zip file containing two versions of each of 84 data sets, % plus this README file. Each data set is given in comma-delimited ASCII % (.csv) form, and Microsoft Excel (.xls) form. % % NOTICE: These data sets may be used freely for scientific, educational and/or % noncommercial purposes, provided suitable acknowledgment is given (by citing % the above-named reference). % % Further details concerning the book, including information on statistical software % (including sample S-PLUS/R and SAS code), are available at the web site % % http://www.stern.nyu.edu/~jsimonof/AnalCatData % % % Information about the dataset % CLASSTYPE: numeric % CLASSINDEX: last % % % Note: Quotes, Single-Quotes and Backslashes were removed, Blanks replaced % with Underscores % @relation analcatdata-vehicle @attribute Alcohol-related {No,Yes} @attribute Gender {Female,Male} @attribute Type {Passenger,Pedestrian/bicyclist} @attribute Age {0-2,12-13,14-15,3-5,6-8,9-11} @attribute Count INTEGER @data No,Male,Passenger,0-2,747 Yes,Male,Passenger,0-2,276 No,Female,Passenger,0-2,765 Yes,Female,Passenger,0-2,231 No,Male,Pedestrian/bicyclist,0-2,321 Yes,Male,Pedestrian/bicyclist,0-2,47 No,Female,Pedestrian/bicyclist,0-2,216 Yes,Female,Pedestrian/bicyclist,0-2,26 No,Male,Passenger,3-5,629 Yes,Male,Passenger,3-5,243 No,Female,Passenger,3-5,652 Yes,Female,Passenger,3-5,190 No,Male,Pedestrian/bicyclist,3-5,805 Yes,Male,Pedestrian/bicyclist,3-5,62 No,Female,Pedestrian/bicyclist,3-5,350 Yes,Female,Pedestrian/bicyclist,3-5,66 No,Male,Passenger,6-8,512 Yes,Male,Passenger,6-8,178 No,Female,Passenger,6-8,483 Yes,Female,Passenger,6-8,176 No,Male,Pedestrian/bicyclist,6-8,944 Yes,Male,Pedestrian/bicyclist,6-8,62 No,Female,Pedestrian/bicyclist,6-8,384 Yes,Female,Pedestrian/bicyclist,6-8,28 No,Male,Passenger,9-11,453 Yes,Male,Passenger,9-11,163 No,Female,Passenger,9-11,449 Yes,Female,Passenger,9-11,119 No,Male,Pedestrian/bicyclist,9-11,797 Yes,Male,Pedestrian/bicyclist,9-11,70 No,Female,Pedestrian/bicyclist,9-11,340 Yes,Female,Pedestrian/bicyclist,9-11,36 No,Male,Passenger,12-13,464 Yes,Male,Passenger,12-13,138 No,Female,Passenger,12-13,399 Yes,Female,Passenger,12-13,142 No,Male,Pedestrian/bicyclist,12-13,577 Yes,Male,Pedestrian/bicyclist,12-13,72 No,Female,Pedestrian/bicyclist,12-13,218 Yes,Female,Pedestrian/bicyclist,12-13,32 No,Male,Passenger,14-15,1112 Yes,Male,Passenger,14-15,369 No,Female,Passenger,14-15,986 Yes,Female,Passenger,14-15,389 No,Male,Pedestrian/bicyclist,14-15,541 Yes,Male,Pedestrian/bicyclist,14-15,121 No,Female,Pedestrian/bicyclist,14-15,220 Yes,Female,Pedestrian/bicyclist,14-15,59