{"id":6823,"date":"2026-11-04T13:41:11","date_gmt":"2026-11-04T05:41:11","guid":{"rendered":"https:\/\/bap2.cm.nsysu.edu.tw\/?page_id=6823"},"modified":"2026-11-04T13:41:11","modified_gmt":"2026-11-04T05:41:11","slug":"9-linear-regression-ib533-2026-09","status":"publish","type":"page","link":"https:\/\/bap2.cm.nsysu.edu.tw\/?page_id=6823&lang=en","title":{"rendered":"9. Linear Regression (IB533 2026.09)"},"content":{"rendered":"<h5 style=\"padding-left: 20px;\"><span style=\"font-family: terminal, monaco, monospace;\"><b>Unit Outlines\uff1a<\/b><\/span><\/h5>\n<h6 style=\"padding-left: 60px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6 Predictive Models<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Method and Parameters<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Model and Coefficients<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Specificity vs. Generality<\/span><\/h6>\n<h6 style=\"padding-left: 60px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6 Simple Linear Regression<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Linear Regression in R<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Estimate Model Coefficients<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Drawing Regression Line<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Make Prediction<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Measures Model Accuracy<\/span><\/h6>\n<h6 style=\"padding-left: 60px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6 Multiple Linear Regression<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Coefficients as Random Variables<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Collinearity<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Model Selection<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u3002Difficulties in Multiple Regression<\/span><\/h6>\n<hr \/>\n<h5 style=\"padding-left: 20px;\"><span style=\"font-family: terminal, monaco, monospace;\"><b>Unit Notebook\uff1a<\/b><\/span><\/h5>\n<h6 style=\"padding-left: 60px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6 09A Simple Linear Regression ( <a href=\"https:\/\/bap2.cm.nsysu.edu.tw\/bap2\/2026\/1151ib533\/unit09A.html\">unit09A.html<\/a> )<\/span><\/h6>\n<h6 style=\"padding-left: 60px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6 09B Multiple Linear Regression ( <a href=\"https:\/\/bap2.cm.nsysu.edu.tw\/bap2\/2026\/1151ib533\/unit09B.html\">unit09B.html<\/a> )<\/span><\/h6>\n<hr \/>\n<h5 style=\"padding-left: 20px;\"><span style=\"font-family: terminal, monaco, monospace;\"><b>Google Drive\uff1a\u00a0<\/b><\/span><\/h5>\n<h6 style=\"padding-left: 60px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6 Unit09:\u00a0 [ <a href=\"https:\/\/drive.google.com\/drive\/folders\/1fb2tGdDRNyexYvPor0NX5SCc7-fSTzMn?usp=drive_link\">~\/ib533\/09_Regression\/<\/a> ]<\/span><\/h6>\n<hr \/>\n<h5 style=\"padding-left: 20px;\"><span style=\"font-family: terminal, monaco, monospace;\"><b>Unit09 Assignment\uff1a Due: 2025\/11\/16 (Mon.) 23:59 <\/b><\/span><\/h5>\n<h6 style=\"padding-left: 60px;\"><span style=\"font-family: terminal, monaco, monospace;\"><b>Personal Assignment<\/b>:<\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">Finish the exercises in unit09A &amp; unit09B, knit the html and<\/span><\/h6>\n<h6 style=\"padding-left: 120px;\"><span style=\"font-family: terminal, monaco, monospace;\">upload to folder [ <a href=\"https:\/\/drive.google.com\/drive\/folders\/1QA75pECcijafBQRlhu4DZnGOppCPEW3C?usp=drive_link\">~\/person\/09_regression\/<\/a> ]<\/span><\/h6>\n<h6 style=\"padding-left: 120px;\"><span style=\"font-family: terminal, monaco, monospace;\">with filename &#8220;&lt;Student-ID&gt;_unit09A.html&#8221;<\/span><\/h6>\n<h6 style=\"padding-left: 120px;\"><span style=\"font-family: terminal, monaco, monospace;\">with filename &#8220;&lt;Student-ID&gt;_unit09B.html&#8221;<\/span><\/h6>\n<hr \/>\n<h6 style=\"padding-left: 60px;\"><span style=\"font-family: terminal, monaco, monospace;\"><b>\u53c3\u8003\u9023\u7d50\uff1a<\/b><\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6\u00a0\u00a0<a href=\"https:\/\/www.data-to-viz.com\/\">From Data to Viz<\/a><\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6\u00a0\u00a0<a href=\"https:\/\/bap2.cm.nsysu.edu.tw\/\">Portal of Big Data BA Platform<\/a><\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6\u00a0\u00a0<a href=\"https:\/\/bap2.cm.nsysu.edu.tw\/?page_id=2039&amp;lang=en\">R: Self Learning Roadmap<\/a><\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6\u00a0 John Hopkins: R Programming <a href=\"https:\/\/www.coursera.org\/learn\/r-programming\">online course<\/a><\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6\u00a0\u00a0John Hopkins: R Programming <a href=\"https:\/\/www.cs.upc.edu\/~robert\/teaching\/estadistica\/rprogramming.pdf\">eBook<\/a><\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6\u00a0\u00a0Harvard: Data Science <a href=\"https:\/\/www.edx.org\/professional-certificate\/harvardx-data-science\">online course<\/a><\/span><\/h6>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6\u00a0 Harvard: Data Science <a href=\"https:\/\/rafalab.github.io\/dsbook\/?fbclid=IwAR1x6AsYApxZb5VUIK8KIaUxH-bP6vkOP0KejwCjyajHoDuKHrVlijyzDDc\">ebook<\/a><\/span><\/h6>\n<hr \/>\n<h6 style=\"padding-left: 90px;\"><span style=\"font-family: terminal, monaco, monospace;\">\u25c6 Week07c Video Recording<\/span><\/h6>\n<hr \/>\n","protected":false},"excerpt":{"rendered":"<p>Unit Outlines\uff1a \u25c6 Predictive Models \u3002Method and Parameters \u3002Model and Coefficients \u3002Specificity vs. Generality \u25c6 Simple Linear Regression \u3002Linear Regression in R \u3002Estimate Model Coefficients \u3002Drawing Regression Line \u3002Make Prediction \u3002Measures Model Accuracy \u25c6 Multiple Linear Regression \u3002Coefficients as Random Variables \u3002Collinearity \u3002Model Selection \u3002Difficulties in Multiple Regression Unit Notebook\uff1a \u25c6 09A Simple Linear Regression ( unit09A.html ) \u25c6 09B Multiple Linear Regression ( unit09B.html ) Google Drive\uff1a\u00a0 \u25c6 Unit09:\u00a0 [ ~\/ib533\/09_Regression\/ ] Unit09 Assignment\uff1a Due: 2025\/11\/16 (Mon.) 23:59 Personal Assignment: Finish the exercises in unit09A &amp; unit09B, knit the html and upload to folder [ ~\/person\/09_regression\/ ] with filename &#8220;&lt;Student-ID&gt;_unit09A.html&#8221; with filename &#8220;&lt;Student-ID&gt;_unit09B.html&#8221; \u53c3\u8003\u9023\u7d50\uff1a \u25c6\u00a0\u00a0From Data to Viz \u25c6\u00a0\u00a0Portal of Big Data BA Platform \u25c6\u00a0\u00a0R: Self Learning Roadmap \u25c6\u00a0 John Hopkins: R Programming online course \u25c6\u00a0\u00a0John Hopkins: R Programming eBook \u25c6\u00a0\u00a0Harvard: Data Science online course \u25c6\u00a0 Harvard: Data Science ebook \u25c6 Week07c Video Recording<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-6823","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/bap2.cm.nsysu.edu.tw\/index.php?rest_route=\/wp\/v2\/pages\/6823","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bap2.cm.nsysu.edu.tw\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bap2.cm.nsysu.edu.tw\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bap2.cm.nsysu.edu.tw\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/bap2.cm.nsysu.edu.tw\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=6823"}],"version-history":[{"count":1,"href":"https:\/\/bap2.cm.nsysu.edu.tw\/index.php?rest_route=\/wp\/v2\/pages\/6823\/revisions"}],"predecessor-version":[{"id":6824,"href":"https:\/\/bap2.cm.nsysu.edu.tw\/index.php?rest_route=\/wp\/v2\/pages\/6823\/revisions\/6824"}],"wp:attachment":[{"href":"https:\/\/bap2.cm.nsysu.edu.tw\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6823"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}