{"id":91,"date":"2021-08-29T19:54:24","date_gmt":"2021-08-29T19:54:24","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/?post_type=chapter&#038;p=91"},"modified":"2022-02-03T17:44:36","modified_gmt":"2022-02-03T17:44:36","slug":"summary-of-identifying-unusual-observations-using-the-empirical-rule","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/chapter\/summary-of-identifying-unusual-observations-using-the-empirical-rule\/","title":{"raw":"Summary of Comparing Quantitative Distributions: 3E","rendered":"Summary of Comparing Quantitative Distributions: 3E"},"content":{"raw":"This page would contain resource information like a glossary of terms from the section, key equations, and a reminder of concepts that were covered.\r\n<div class=\"textbox learning-objectives\">\r\n<h3>Essential Concepts<\/h3>\r\n<ul>\r\n \t<li>When describing and summarizing data, the shape of a distribution will need to be frequently described and compared to the center and spread of the distribution of a quantitative variable. The determination of the presence of outliers will also be helpful in summarizing the data.<\/li>\r\n<\/ul>\r\n<\/div>\r\n<h2>Glossary<\/h2>\r\n<dl id=\"fs-id1170572229168\" class=\"definition\">\r\n \t<dt>observational units<\/dt>\r\n \t<dd id=\"fs-id1170572229174\">individuals or items whose characteristics we are interested in.<\/dd>\r\n<\/dl>\r\n<dl id=\"fs-id1170572229190\" class=\"definition\">\r\n \t<dt>variables<\/dt>\r\n \t<dd id=\"fs-id1170572229195\">the characteristics we record on the observational units. These may be quantitative or categorical variables.<\/dd>\r\n<\/dl>\r\nPut formal DCMP I Can statements to prepare for the self-check.\r\n\r\n<span style=\"background-color: #ffff00;\">These I Can Statements are new (the first one is the \u201cyou will understand\u201d rephrased as an I Can):<\/span>\r\n<ul>\r\n \t<li>I can use histograms and dotplots to compare distributions of a quantitative variable across groups.<\/li>\r\n \t<li>I can compare the center, shape, and spread of distributions of a quantitative variable across groups.<\/li>\r\n<\/ul>","rendered":"<p>This page would contain resource information like a glossary of terms from the section, key equations, and a reminder of concepts that were covered.<\/p>\n<div class=\"textbox learning-objectives\">\n<h3>Essential Concepts<\/h3>\n<ul>\n<li>When describing and summarizing data, the shape of a distribution will need to be frequently described and compared to the center and spread of the distribution of a quantitative variable. The determination of the presence of outliers will also be helpful in summarizing the data.<\/li>\n<\/ul>\n<\/div>\n<h2>Glossary<\/h2>\n<dl id=\"fs-id1170572229168\" class=\"definition\">\n<dt>observational units<\/dt>\n<dd id=\"fs-id1170572229174\">individuals or items whose characteristics we are interested in.<\/dd>\n<\/dl>\n<dl id=\"fs-id1170572229190\" class=\"definition\">\n<dt>variables<\/dt>\n<dd id=\"fs-id1170572229195\">the characteristics we record on the observational units. These may be quantitative or categorical variables.<\/dd>\n<\/dl>\n<p>Put formal DCMP I Can statements to prepare for the self-check.<\/p>\n<p><span style=\"background-color: #ffff00;\">These I Can Statements are new (the first one is the \u201cyou will understand\u201d rephrased as an I Can):<\/span><\/p>\n<ul>\n<li>I can use histograms and dotplots to compare distributions of a quantitative variable across groups.<\/li>\n<li>I can compare the center, shape, and spread of distributions of a quantitative variable across groups.<\/li>\n<\/ul>\n","protected":false},"author":17533,"menu_order":34,"template":"","meta":{"_candela_citation":"[]","CANDELA_OUTCOMES_GUID":"","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-91","chapter","type-chapter","status-publish","hentry"],"part":3,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/91","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/users\/17533"}],"version-history":[{"count":10,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/91\/revisions"}],"predecessor-version":[{"id":2779,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/91\/revisions\/2779"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/parts\/3"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/91\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/media?parent=91"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapter-type?post=91"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/contributor?post=91"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/license?post=91"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}