{"id":165,"date":"2017-04-15T03:18:23","date_gmt":"2017-04-15T03:18:23","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/conceptstest1\/chapter\/scatterplots-5-of-5\/"},"modified":"2020-01-22T00:56:23","modified_gmt":"2020-01-22T00:56:23","slug":"scatterplots-5-of-5","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/chapter\/scatterplots-5-of-5\/","title":{"raw":"Scatterplots (5 of 5)","rendered":"Scatterplots (5 of 5)"},"content":{"raw":"<div class=\"textbox learning-objectives\">\r\n<h3>Learning OUTCOMES<\/h3>\r\n<ul>\r\n \t<li>Use a scatterplot to display the relationship between two quantitative variables. Describe the overall pattern (form, direction, and strength) and striking deviations from the pattern.<\/li>\r\n<\/ul>\r\n<\/div>\r\n<h2>Labeling Groups in a Scatterplot<\/h2>\r\nIf we graph data from two or more groups in a scatterplot, the relationship between the two quantitative variables can be hidden or unclear. We can use a categorical variable to label groups within the scatterplot, then look for patterns within each group. The relationship may be clearer within each group.\r\n<div class=\"textbox exercises\">\r\n<h3>Example<\/h3>\r\n<h2>Hot Dogs<\/h2>\r\nA study was conducted by a concerned health group in which 54 major hot dog brands were examined. Using this data, we explore the relationship between sodium content and calories. We begin by making a scatterplot with data from the three types of hot dogs: beef, poultry, and meat (meat is a combination of pork, beef, and poultry).\r\n\r\nhttps:\/\/youtu.be\/teS5d2s8PS8\r\n\r\n<\/div>\r\n<h2>Let\u2019s Summarize<\/h2>\r\n<ul>\r\n \t<li>The relationship between two quantitative variables is visually displayed using the scatterplot, where each point represents an individual. We always plot the explanatory variable on the horizontal x-axis and the response variable on the vertical y-axis.<\/li>\r\n \t<li>When we explore a relationship using the scatterplot, we should describe the <em>overall pattern<\/em> of the relationship and any <em>deviations<\/em> from that pattern. To describe the overall pattern, consider the <em>direction<\/em>, <em>form<\/em>, and <em>strength<\/em> of the relationship. Assessing the strength just by looking at the scatterplot can be problematic; using a numerical measure to determine strength is discussed later in this course.<\/li>\r\n \t<li>Adding labels to the scatterplot that indicate different groups or categories within the data might help us gain more insight about the relationship we are exploring.<\/li>\r\n<\/ul>\r\n<h2>Contribute!<\/h2><div style=\"margin-bottom: 8px;\">Did you have an idea for improving this content? We\u2019d love your input.<\/div><a href=\"https:\/\/docs.google.com\/document\/d\/1Lf2hmTdoNilRfxSBwOgzlROeOs9A248YCVkhte1TE1E\" target=\"_blank\" style=\"font-size: 10pt; font-weight: 600; color: #077fab; text-decoration: none; border: 2px solid #077fab; border-radius: 7px; padding: 5px 25px; text-align: center; cursor: pointer; line-height: 1.5em;\">Improve this page<\/a><a style=\"margin-left: 16px;\" target=\"_blank\" href=\"https:\/\/docs.google.com\/document\/d\/1vy-T6DtTF-BbMfpVEI7VP_R7w2A4anzYZLXR8Pk4Fu4\">Learn More<\/a>","rendered":"<div class=\"textbox learning-objectives\">\n<h3>Learning OUTCOMES<\/h3>\n<ul>\n<li>Use a scatterplot to display the relationship between two quantitative variables. Describe the overall pattern (form, direction, and strength) and striking deviations from the pattern.<\/li>\n<\/ul>\n<\/div>\n<h2>Labeling Groups in a Scatterplot<\/h2>\n<p>If we graph data from two or more groups in a scatterplot, the relationship between the two quantitative variables can be hidden or unclear. We can use a categorical variable to label groups within the scatterplot, then look for patterns within each group. The relationship may be clearer within each group.<\/p>\n<div class=\"textbox exercises\">\n<h3>Example<\/h3>\n<h2>Hot Dogs<\/h2>\n<p>A study was conducted by a concerned health group in which 54 major hot dog brands were examined. Using this data, we explore the relationship between sodium content and calories. We begin by making a scatterplot with data from the three types of hot dogs: beef, poultry, and meat (meat is a combination of pork, beef, and poultry).<\/p>\n<p><iframe loading=\"lazy\" id=\"oembed-1\" title=\"Creating a Labeled Scatterplot\" width=\"500\" height=\"375\" src=\"https:\/\/www.youtube.com\/embed\/teS5d2s8PS8?feature=oembed&#38;rel=0\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<\/div>\n<h2>Let\u2019s Summarize<\/h2>\n<ul>\n<li>The relationship between two quantitative variables is visually displayed using the scatterplot, where each point represents an individual. We always plot the explanatory variable on the horizontal x-axis and the response variable on the vertical y-axis.<\/li>\n<li>When we explore a relationship using the scatterplot, we should describe the <em>overall pattern<\/em> of the relationship and any <em>deviations<\/em> from that pattern. To describe the overall pattern, consider the <em>direction<\/em>, <em>form<\/em>, and <em>strength<\/em> of the relationship. Assessing the strength just by looking at the scatterplot can be problematic; using a numerical measure to determine strength is discussed later in this course.<\/li>\n<li>Adding labels to the scatterplot that indicate different groups or categories within the data might help us gain more insight about the relationship we are exploring.<\/li>\n<\/ul>\n<h2>Contribute!<\/h2>\n<div style=\"margin-bottom: 8px;\">Did you have an idea for improving this content? We\u2019d love your input.<\/div>\n<p><a href=\"https:\/\/docs.google.com\/document\/d\/1Lf2hmTdoNilRfxSBwOgzlROeOs9A248YCVkhte1TE1E\" target=\"_blank\" style=\"font-size: 10pt; font-weight: 600; color: #077fab; text-decoration: none; border: 2px solid #077fab; border-radius: 7px; padding: 5px 25px; text-align: center; cursor: pointer; line-height: 1.5em;\">Improve this page<\/a><a style=\"margin-left: 16px;\" target=\"_blank\" href=\"https:\/\/docs.google.com\/document\/d\/1vy-T6DtTF-BbMfpVEI7VP_R7w2A4anzYZLXR8Pk4Fu4\">Learn More<\/a><\/p>\n\n\t\t\t <section class=\"citations-section\" role=\"contentinfo\">\n\t\t\t <h3>Candela Citations<\/h3>\n\t\t\t\t\t <div>\n\t\t\t\t\t\t <div id=\"citation-list-165\">\n\t\t\t\t\t\t\t <div class=\"licensing\"><div class=\"license-attribution-dropdown-subheading\">CC licensed content, Shared previously<\/div><ul class=\"citation-list\"><li>Concepts in Statistics. <strong>Provided by<\/strong>: Open Learning Initiative. <strong>Located at<\/strong>: <a target=\"_blank\" href=\"http:\/\/oli.cmu.edu\">http:\/\/oli.cmu.edu<\/a>. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em><\/li><\/ul><\/div>\n\t\t\t\t\t\t <\/div>\n\t\t\t\t\t <\/div>\n\t\t\t <\/section>","protected":false},"author":163,"menu_order":7,"template":"","meta":{"_candela_citation":"[{\"type\":\"cc\",\"description\":\"Concepts in Statistics\",\"author\":\"\",\"organization\":\"Open Learning Initiative\",\"url\":\"http:\/\/oli.cmu.edu\",\"project\":\"\",\"license\":\"cc-by\",\"license_terms\":\"\"}]","CANDELA_OUTCOMES_GUID":"8e621db5-39b0-4a3b-bb2c-6888a6274c31, 01f82408-a0e8-4b13-b273-db47828f6d04","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-165","chapter","type-chapter","status-publish","hentry"],"part":140,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/pressbooks\/v2\/chapters\/165","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/wp\/v2\/users\/163"}],"version-history":[{"count":4,"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/pressbooks\/v2\/chapters\/165\/revisions"}],"predecessor-version":[{"id":2265,"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/pressbooks\/v2\/chapters\/165\/revisions\/2265"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/pressbooks\/v2\/parts\/140"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/pressbooks\/v2\/chapters\/165\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/wp\/v2\/media?parent=165"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/pressbooks\/v2\/chapter-type?post=165"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/wp\/v2\/contributor?post=165"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/wm-concepts-statistics\/wp-json\/wp\/v2\/license?post=165"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}