{"id":4526,"date":"2022-04-13T14:07:13","date_gmt":"2022-04-13T14:07:13","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/?post_type=chapter&#038;p=4526"},"modified":"2022-05-10T19:59:03","modified_gmt":"2022-05-10T19:59:03","slug":"instructor-guide-6e-corequisite-support","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/chapter\/instructor-guide-6e-corequisite-support\/","title":{"raw":"Instructor Guide 6E: Corequisite Support","rendered":"Instructor Guide 6E: Corequisite Support"},"content":{"raw":"<em>While this support activity is designed for a face-to-face, synchronous delivery, it should be noted that supporting text and interactive examples have been embedded in the digital assignment page to assist asynchronous or hybrid course delivery and to be made more accessible to students performing make-up work.<\/em>\r\n<h2>Notes for synchronous active-learning delivery<\/h2>\r\nThe purpose of this corequisite support activity is to provide additional practice and\u00a0assess students\u2019 abilities to:\r\n<ul>\r\n \t<li>Use technology to make a scatterplot.<\/li>\r\n \t<li>Use technology to calculate a line of best fit.<\/li>\r\n \t<li>Interpret the slope and intercept of the line of best fit.<\/li>\r\n<\/ul>\r\nStudents will need these skills in order to complete Preview Assignment and In-Class\u00a0Activity 6.E.\r\n\r\nThe suggested technology for this support activity is the DCMP Linear Regression tool\u00a0at <a href=\"https:\/\/dcmathpathways.shinyapps.io\/LinearRegression\/\">https:\/\/dcmathpathways.shinyapps.io\/LinearRegression\/<\/a>.\r\n\r\nStudents can complete all of the questions in this support activity using the <strong>Fit Linear\u00a0Regression Model<\/strong> tab. Students may calculate predicted values directly from the\u00a0equation of the line or using the \u201cFind Predicted Value\u201d functionality in the sidebar of the\u00a0tool.\r\n\r\nStudents may obtain the scatterplot of residuals versus predicted values for Question 3\u00a0from the <strong>Fitted Values &amp; Residual Analysis<\/strong> tab.","rendered":"<p><em>While this support activity is designed for a face-to-face, synchronous delivery, it should be noted that supporting text and interactive examples have been embedded in the digital assignment page to assist asynchronous or hybrid course delivery and to be made more accessible to students performing make-up work.<\/em><\/p>\n<h2>Notes for synchronous active-learning delivery<\/h2>\n<p>The purpose of this corequisite support activity is to provide additional practice and\u00a0assess students\u2019 abilities to:<\/p>\n<ul>\n<li>Use technology to make a scatterplot.<\/li>\n<li>Use technology to calculate a line of best fit.<\/li>\n<li>Interpret the slope and intercept of the line of best fit.<\/li>\n<\/ul>\n<p>Students will need these skills in order to complete Preview Assignment and In-Class\u00a0Activity 6.E.<\/p>\n<p>The suggested technology for this support activity is the DCMP Linear Regression tool\u00a0at <a href=\"https:\/\/dcmathpathways.shinyapps.io\/LinearRegression\/\">https:\/\/dcmathpathways.shinyapps.io\/LinearRegression\/<\/a>.<\/p>\n<p>Students can complete all of the questions in this support activity using the <strong>Fit Linear\u00a0Regression Model<\/strong> tab. Students may calculate predicted values directly from the\u00a0equation of the line or using the \u201cFind Predicted Value\u201d functionality in the sidebar of the\u00a0tool.<\/p>\n<p>Students may obtain the scatterplot of residuals versus predicted values for Question 3\u00a0from the <strong>Fitted Values &amp; Residual Analysis<\/strong> tab.<\/p>\n","protected":false},"author":25777,"menu_order":9,"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-4526","chapter","type-chapter","status-publish","hentry"],"part":4483,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/4526","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\/25777"}],"version-history":[{"count":4,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/4526\/revisions"}],"predecessor-version":[{"id":4690,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/4526\/revisions\/4690"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/parts\/4483"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/4526\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/media?parent=4526"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapter-type?post=4526"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/contributor?post=4526"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/license?post=4526"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}