{"id":5244,"date":"2016-05-07T11:22:10","date_gmt":"2016-05-07T16:22:10","guid":{"rendered":"http:\/\/www.ssc.wisc.edu\/~jfrees\/?page_id=5244"},"modified":"2016-05-10T19:42:26","modified_gmt":"2016-05-11T00:42:26","slug":"qualitative-variables","status":"publish","type":"page","link":"https:\/\/users.ssc.wisc.edu\/~ewfrees\/loss-data-analytics\/introduction-to-loss-data-analytics\/variable-types\/qualitative-variables\/","title":{"rendered":"Qualitative Variables"},"content":{"rendered":"

Let us start with the simplest type, a binary variable. As suggested by its name, a binary variable<\/em> is one with only two possible values. Although not necessary, the two values are commonly taken to be a “0” and a “1.” Binary variables are typically used to indicate whether or not an entity possesses an attribute. For example, we might code a variable to be a “1” if an insured is female and a “0” if male. (An insured<\/em> is a person who is covered under an insurance agreement.) <\/p>\n

More generally, a qualitative<\/em>, or categorical<\/em>, variable is one for which the measurement denotes membership in a set of groups, or categories. For example, if you were coding in which area of the country in which an insured resides, you might use a “1” for the northern part, “2” for southern, and “3” for everything else. A binary variable is a special type of categorical variable where there are only two categories. This location variable is an example of a nominal<\/em> variable, one for which the levels have no natural ordering. Any analysis of nominal variables should not depend on the labeling of the categories. For example, instead of using a “1,2,3” for “north, south, other”, I should arrive at the same set of summary statistics if I used a “2,1,3” coding instead, interchanging north and south. <\/p>\n

In contrast, an ordinal<\/em> variable is a type of categorical variable for which an ordering does exist. For example, with a survey to see how satisfied customers are with our claims servicing department, we might use a five point scale that ranges from “1” meaning “dissatisfied” to a “5” meaning “satisfied.” Ordinal variables provide a clear ordering of levels of a variable but the amount of separation between levels is unknown. <\/p>\n

◄ Previous page<\/a><\/div>
Next page ►<\/a><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"

Let us start with the simplest type, a binary variable. As suggested by its name, a binary variable is one with only two possible values. Although not necessary, the two values are commonly taken to …<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":5239,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":{"jetpack_post_was_ever_published":false},"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/P8cLPd-1mA","acf":[],"_links":{"self":[{"href":"https:\/\/users.ssc.wisc.edu\/~ewfrees\/wp-json\/wp\/v2\/pages\/5244"}],"collection":[{"href":"https:\/\/users.ssc.wisc.edu\/~ewfrees\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/users.ssc.wisc.edu\/~ewfrees\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/users.ssc.wisc.edu\/~ewfrees\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/users.ssc.wisc.edu\/~ewfrees\/wp-json\/wp\/v2\/comments?post=5244"}],"version-history":[{"count":3,"href":"https:\/\/users.ssc.wisc.edu\/~ewfrees\/wp-json\/wp\/v2\/pages\/5244\/revisions"}],"predecessor-version":[{"id":5380,"href":"https:\/\/users.ssc.wisc.edu\/~ewfrees\/wp-json\/wp\/v2\/pages\/5244\/revisions\/5380"}],"up":[{"embeddable":true,"href":"https:\/\/users.ssc.wisc.edu\/~ewfrees\/wp-json\/wp\/v2\/pages\/5239"}],"wp:attachment":[{"href":"https:\/\/users.ssc.wisc.edu\/~ewfrees\/wp-json\/wp\/v2\/media?parent=5244"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}