{"id":3707,"date":"2023-12-08T15:29:31","date_gmt":"2023-12-08T14:29:31","guid":{"rendered":"https:\/\/www.psyctc.org\/psyctc\/?post_type=docs&p=3707"},"modified":"2024-05-06T09:19:13","modified_gmt":"2024-05-06T07:19:13","password":"","slug":"cumulative-distribution","status":"publish","type":"docs","link":"https:\/\/www.psyctc.org\/psyctc\/glossary2\/cumulative-distribution\/","title":{"rendered":"Cumulative distribution"},"content":{"rendered":"\n

It’s pretty much what it says: putting the data you have in order so that the counts mount up to the total number of observations you have. It’s a fairly familiar way of tabulating things but a less familiar way of plotting them but it can be a very helpful way to plot as well as to tabulate and it underpins a lot of the ways that statisticians think about and model distributions.<\/p>\n\n\n\n

Details<\/h4>\n\n\n\n

Suppose you have some data like this.<\/p>\n\n\n\n

\n \n \n\n \n \n \n \n\n\n scores<\/th> <\/tr>\n<\/thead>\n \n\n \n \n\n\n
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0.50<\/td>\n <\/tr>\n
2.50<\/td>\n <\/tr>\n
2.40<\/td>\n <\/tr>\n
2.50<\/td>\n <\/tr>\n
3.40<\/td>\n <\/tr>\n
2.60<\/td>\n <\/tr>\n
0.00<\/td>\n <\/tr>\n
0.90<\/td>\n <\/tr>\n <\/tbody> \n\n \n \n \n <\/table>\n\n<\/div>