{"id":231,"date":"2023-02-20T17:13:47","date_gmt":"2023-02-20T17:13:47","guid":{"rendered":"https:\/\/content.one.lumenlearning.com\/introstatstest\/chapter\/scatterplots-learn-it-2\/"},"modified":"2025-05-11T23:09:30","modified_gmt":"2025-05-11T23:09:30","slug":"scatterplots-learn-it-2","status":"publish","type":"chapter","link":"https:\/\/content.one.lumenlearning.com\/introstatstest\/chapter\/scatterplots-learn-it-2\/","title":{"raw":"Scatterplots &amp; Correlation Coefficients: Learn It 2","rendered":"Scatterplots &amp; Correlation Coefficients: Learn It 2"},"content":{"raw":"<section class=\"textbox learningGoals\">\r\n<ul>\r\n\t<li>Create scatterplots for bivariate data and answer questions from the graph.<\/li>\r\n\t<li>Describe the trend of bivariate data.<\/li>\r\n\t<li>Calculate the correlation coefficient and explain what it means.<\/li>\r\n<\/ul>\r\n<\/section>\r\n<h2>Interpreting a Scatterplot<\/h2>\r\n<p>How do we describe the relationship between two quantitative variables using a scatterplot? We describe the overall pattern and deviations from that pattern. To describe the overall pattern of the distribution of one quantitative variable, we describe the shape, center, and spread. We also describe deviations from the pattern (outliers).<\/p>\r\n<div class=\"wp-nocaption alignnone\">\r\n[caption id=\"attachment_403\" align=\"aligncenter\" width=\"300\"]<img class=\"wp-image-403 size-medium\" src=\"https:\/\/content-cdn.one.lumenlearning.com\/wp-content\/uploads\/sites\/27\/2023\/02\/23223043\/5.1.L.Diagram1-1-300x250.png\" alt=\"Flowchart of graphing the distribution of 2 quantitative variables in a scatterplot, which includes overall patterns and derivations from the patterns\" width=\"300\" height=\"250\" \/> Figure 1. When analyzing a dotplot, describe the overall pattern (direction, form, strength) and look for deviations, or outliers, that don\u2019t follow the pattern.[\/caption]\r\n<\/div>\r\n<p>Similarly, in a scatterplot, we describe the overall pattern with descriptions of\u00a0<strong>direction (trend)<\/strong>,\u00a0<strong>form (linear or non-linear)<\/strong>, and\u00a0<strong>strength<\/strong>. Deviations from the pattern are still called <strong>outliers<\/strong>.<\/p>\r\n<h3>Identifying Trends\/Directions<\/h3>\r\n<p>Identifying patterns in scatterplots can help us determine if a relationship exists between two variables. Scatterplots might show positive trends, negative trends, or no trends at all.<\/p>\r\n<section class=\"textbox proTip\">A scatterplot shows a <strong>positive trend<\/strong> if the response variable (represented on the vertical axis) tends to increase as the explanatory variable (represented on the horizontal axis) increases. Conversely, if the response variable tends to decrease as the explanatory variable increases, then the scatterplot shows a <strong>negative trend.<\/strong><\/section>\r\n<section class=\"textbox tryIt\">[ohm2_question hide_question_numbers=1]1138[\/ohm2_question]<\/section>","rendered":"<section class=\"textbox learningGoals\">\n<ul>\n<li>Create scatterplots for bivariate data and answer questions from the graph.<\/li>\n<li>Describe the trend of bivariate data.<\/li>\n<li>Calculate the correlation coefficient and explain what it means.<\/li>\n<\/ul>\n<\/section>\n<h2>Interpreting a Scatterplot<\/h2>\n<p>How do we describe the relationship between two quantitative variables using a scatterplot? We describe the overall pattern and deviations from that pattern. To describe the overall pattern of the distribution of one quantitative variable, we describe the shape, center, and spread. We also describe deviations from the pattern (outliers).<\/p>\n<div class=\"wp-nocaption alignnone\">\n<figure id=\"attachment_403\" aria-describedby=\"caption-attachment-403\" style=\"width: 300px\" class=\"wp-caption aligncenter\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-403 size-medium\" src=\"https:\/\/content-cdn.one.lumenlearning.com\/wp-content\/uploads\/sites\/27\/2023\/02\/23223043\/5.1.L.Diagram1-1-300x250.png\" alt=\"Flowchart of graphing the distribution of 2 quantitative variables in a scatterplot, which includes overall patterns and derivations from the patterns\" width=\"300\" height=\"250\" srcset=\"https:\/\/content-cdn.one.lumenlearning.com\/wp-content\/uploads\/sites\/27\/2023\/02\/23223043\/5.1.L.Diagram1-1-300x250.png 300w, https:\/\/content-cdn.one.lumenlearning.com\/wp-content\/uploads\/sites\/27\/2023\/02\/23223043\/5.1.L.Diagram1-1-65x54.png 65w, https:\/\/content-cdn.one.lumenlearning.com\/wp-content\/uploads\/sites\/27\/2023\/02\/23223043\/5.1.L.Diagram1-1-225x187.png 225w, https:\/\/content-cdn.one.lumenlearning.com\/wp-content\/uploads\/sites\/27\/2023\/02\/23223043\/5.1.L.Diagram1-1-350x291.png 350w, https:\/\/content-cdn.one.lumenlearning.com\/wp-content\/uploads\/sites\/27\/2023\/02\/23223043\/5.1.L.Diagram1-1.png 607w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><figcaption id=\"caption-attachment-403\" class=\"wp-caption-text\">Figure 1. When analyzing a dotplot, describe the overall pattern (direction, form, strength) and look for deviations, or outliers, that don\u2019t follow the pattern.<\/figcaption><\/figure>\n<\/div>\n<p>Similarly, in a scatterplot, we describe the overall pattern with descriptions of\u00a0<strong>direction (trend)<\/strong>,\u00a0<strong>form (linear or non-linear)<\/strong>, and\u00a0<strong>strength<\/strong>. Deviations from the pattern are still called <strong>outliers<\/strong>.<\/p>\n<h3>Identifying Trends\/Directions<\/h3>\n<p>Identifying patterns in scatterplots can help us determine if a relationship exists between two variables. Scatterplots might show positive trends, negative trends, or no trends at all.<\/p>\n<section class=\"textbox proTip\">A scatterplot shows a <strong>positive trend<\/strong> if the response variable (represented on the vertical axis) tends to increase as the explanatory variable (represented on the horizontal axis) increases. Conversely, if the response variable tends to decrease as the explanatory variable increases, then the scatterplot shows a <strong>negative trend.<\/strong><\/section>\n<section class=\"textbox tryIt\"><iframe loading=\"lazy\" id=\"ohm1138\" class=\"resizable\" src=\"https:\/\/ohm.one.lumenlearning.com\/multiembedq.php?id=1138&theme=lumen&iframe_resize_id=ohm1138&source=tnh\" width=\"100%\" height=\"150\"><\/iframe><\/section>\n","protected":false},"author":12,"menu_order":7,"template":"","meta":{"_candela_citation":"[]","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"part":225,"module-header":"learn_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\/introstatstest\/wp-json\/pressbooks\/v2\/chapters\/231"}],"collection":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/wp\/v2\/users\/12"}],"version-history":[{"count":10,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapters\/231\/revisions"}],"predecessor-version":[{"id":6647,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapters\/231\/revisions\/6647"}],"part":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/parts\/225"}],"metadata":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapters\/231\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/wp\/v2\/media?parent=231"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/pressbooks\/v2\/chapter-type?post=231"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/wp\/v2\/contributor?post=231"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/content.one.lumenlearning.com\/introstatstest\/wp-json\/wp\/v2\/license?post=231"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}