{"id":8261,"date":"2023-09-29T14:26:41","date_gmt":"2023-09-29T14:26:41","guid":{"rendered":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/?post_type=chapter&#038;p=8261"},"modified":"2023-12-01T18:16:36","modified_gmt":"2023-12-01T18:16:36","slug":"modeling-logistic-growth-apply-it-2","status":"publish","type":"chapter","link":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/chapter\/modeling-logistic-growth-apply-it-2\/","title":{"raw":"Modeling Logistic Growth: Apply It 2","rendered":"Modeling Logistic Growth: Apply It 2"},"content":{"raw":"<h2>Understanding and Applying Logistic Growth Models Cont.<\/h2>\r\nMoving from the technology adoption landscape, we proceed to an urban context. The final scenario invites you to apply logistic growth models to urban population growth, a complex and critical area of study for urban planners. This transition highlights the wide-ranging applicability of logistic models, from product markets to city planning.\r\n<h3>Scenario 3: Urban Population Growth<\/h3>\r\nUrban planners are analyzing the growth of a city's population. They believe the growth follows a logistic model due to constraints like housing and infrastructure.\r\n<section class=\"textbox tryIt\">\r\n<p>[ohm2_question hide_question_numbers=1]13949[\/ohm2_question]<\/p>\r\n<\/section>\r\n<section class=\"textbox tryIt\">\r\n<p>[ohm2_question hide_question_numbers=1]13950[\/ohm2_question]<\/p>\r\n<\/section>\r\nAs you conclude this Apply It section, reflect on the diverse applications of logistic growth models you've encountered. These models provide crucial insights into growth dynamics in various fields. Consider how understanding the limits of growth, represented by carrying capacity, and the rate of growth is essential for predicting and managing future developments in both natural and human-made environments. Amazing work today!","rendered":"<h2>Understanding and Applying Logistic Growth Models Cont.<\/h2>\n<p>Moving from the technology adoption landscape, we proceed to an urban context. The final scenario invites you to apply logistic growth models to urban population growth, a complex and critical area of study for urban planners. This transition highlights the wide-ranging applicability of logistic models, from product markets to city planning.<\/p>\n<h3>Scenario 3: Urban Population Growth<\/h3>\n<p>Urban planners are analyzing the growth of a city&#8217;s population. They believe the growth follows a logistic model due to constraints like housing and infrastructure.<\/p>\n<section class=\"textbox tryIt\">\n<iframe loading=\"lazy\" id=\"ohm13949\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=13949&theme=lumen&iframe_resize_id=ohm13949&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><br \/>\n<\/section>\n<section class=\"textbox tryIt\">\n<iframe loading=\"lazy\" id=\"ohm13950\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=13950&theme=lumen&iframe_resize_id=ohm13950&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><br \/>\n<\/section>\n<p>As you conclude this Apply It section, reflect on the diverse applications of logistic growth models you&#8217;ve encountered. These models provide crucial insights into growth dynamics in various fields. Consider how understanding the limits of growth, represented by carrying capacity, and the rate of growth is essential for predicting and managing future developments in both natural and human-made environments. Amazing work today!<\/p>\n","protected":false},"author":15,"menu_order":19,"template":"","meta":{"_candela_citation":"[]","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"part":8093,"module-header":"apply_it","content_attributions":[],"internal_book_links":[],"video_content":null,"cc_video_embed_content":{"cc_scripts":"","media_targets":[]},"try_it_collection":null,"_links":{"self":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8261"}],"collection":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/users\/15"}],"version-history":[{"count":3,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8261\/revisions"}],"predecessor-version":[{"id":12171,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8261\/revisions\/12171"}],"part":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/parts\/8093"}],"metadata":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapters\/8261\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/media?parent=8261"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/pressbooks\/v2\/chapter-type?post=8261"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/contributor?post=8261"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/quantitativereasoning\/wp-json\/wp\/v2\/license?post=8261"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}