{"id":430,"date":"2021-12-20T14:27:30","date_gmt":"2021-12-20T14:27:30","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/?post_type=chapter&#038;p=430"},"modified":"2022-02-11T21:06:42","modified_gmt":"2022-02-11T21:06:42","slug":"summary-of-4a","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/chapter\/summary-of-4a\/","title":{"raw":"Summary of Calculating Mean and Median of a Dataset: 4A","rendered":"Summary of Calculating Mean and Median of a Dataset: 4A"},"content":{"raw":"This page would contain resource information like a glossary of terms from the section, key equations, and a reminder of concepts that were covered.\r\n\r\nMake this more relevant to what students want -- help them to build their processes, study guides, mnemonics, and memory dump material.\r\n<div class=\"textbox learning-objectives\">\r\n<h3>Essential Concepts<\/h3>\r\n<ul>\r\n \t<li>The mean of a dataset can be computed by summing the data values and dividing by the number of values.<\/li>\r\n \t<li>The median of a dataset can be computed by ordering the data values and identifying the value in \"the middle\".<\/li>\r\n \t<li>The mean represents the balance point of the data, and the median represents the 50<sup>th<\/sup> percentile, or the value that splits the data in half.<\/li>\r\n<\/ul>\r\n<\/div>\r\n<h2>Key Equations<\/h2>\r\n<ul>\r\n \t<li><strong>Mean<\/strong><\/li>\r\n<\/ul>\r\n[latex]\\dfrac{\\text{sum of data values}}{\\text{total number of data values}}[\/latex]\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0or\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 [latex]\\bar{x}=\\dfrac{\\sum{x}}{n}[\/latex]\r\n\r\nwhere\u00a0[latex]\\bar{x}[\/latex] is the mean, [latex]{\\sum{x}}[\/latex] is the symbol for \"sum of\", [latex]{x}[\/latex] represents the data values, and [latex]{n}[\/latex] is the total number of data values.\r\n<h2>Glossary<\/h2>\r\n<dl id=\"fs-id1170572229168\" class=\"definition\">\r\n \t<dt>mean<\/dt>\r\n \t<dd id=\"fs-id1170572229174\">the arithmetic mean of a list of numbers, commonly called the \"average\".<\/dd>\r\n<\/dl>\r\n<dl id=\"fs-id1170572229190\" class=\"definition\">\r\n \t<dt>median<\/dt>\r\n \t<dd id=\"fs-id1170572229195\">the \"middlemost\" number.<\/dd>\r\n<\/dl>\r\nPut formal DCMP I Can statements to prepare for the self-check.\r\n\r\n<span style=\"background-color: #ffff00;\">These I Can Statements are new (the first one is the \"you will understand\" rephrased as an I Can):<\/span>\r\n<ul>\r\n \t<li>I can use the mean and median as numerical measures to represent the \"center\" of quantitative data.<\/li>\r\n \t<li>I can calculate the mean and median with technology to make comparisons between groups.<\/li>\r\n \t<li>I can make connections between the measures of center and graphical representations of data (e.g., histogram).<\/li>\r\n<\/ul>","rendered":"<p>This page would contain resource information like a glossary of terms from the section, key equations, and a reminder of concepts that were covered.<\/p>\n<p>Make this more relevant to what students want &#8212; help them to build their processes, study guides, mnemonics, and memory dump material.<\/p>\n<div class=\"textbox learning-objectives\">\n<h3>Essential Concepts<\/h3>\n<ul>\n<li>The mean of a dataset can be computed by summing the data values and dividing by the number of values.<\/li>\n<li>The median of a dataset can be computed by ordering the data values and identifying the value in &#8220;the middle&#8221;.<\/li>\n<li>The mean represents the balance point of the data, and the median represents the 50<sup>th<\/sup> percentile, or the value that splits the data in half.<\/li>\n<\/ul>\n<\/div>\n<h2>Key Equations<\/h2>\n<ul>\n<li><strong>Mean<\/strong><\/li>\n<\/ul>\n<p>[latex]\\dfrac{\\text{sum of data values}}{\\text{total number of data values}}[\/latex]\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0or\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 [latex]\\bar{x}=\\dfrac{\\sum{x}}{n}[\/latex]<\/p>\n<p>where\u00a0[latex]\\bar{x}[\/latex] is the mean, [latex]{\\sum{x}}[\/latex] is the symbol for &#8220;sum of&#8221;, [latex]{x}[\/latex] represents the data values, and [latex]{n}[\/latex] is the total number of data values.<\/p>\n<h2>Glossary<\/h2>\n<dl id=\"fs-id1170572229168\" class=\"definition\">\n<dt>mean<\/dt>\n<dd id=\"fs-id1170572229174\">the arithmetic mean of a list of numbers, commonly called the &#8220;average&#8221;.<\/dd>\n<\/dl>\n<dl id=\"fs-id1170572229190\" class=\"definition\">\n<dt>median<\/dt>\n<dd id=\"fs-id1170572229195\">the &#8220;middlemost&#8221; number.<\/dd>\n<\/dl>\n<p>Put formal DCMP I Can statements to prepare for the self-check.<\/p>\n<p><span style=\"background-color: #ffff00;\">These I Can Statements are new (the first one is the &#8220;you will understand&#8221; rephrased as an I Can):<\/span><\/p>\n<ul>\n<li>I can use the mean and median as numerical measures to represent the &#8220;center&#8221; of quantitative data.<\/li>\n<li>I can calculate the mean and median with technology to make comparisons between groups.<\/li>\n<li>I can make connections between the measures of center and graphical representations of data (e.g., histogram).<\/li>\n<\/ul>\n","protected":false},"author":25777,"menu_order":5,"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-430","chapter","type-chapter","status-publish","hentry"],"part":621,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/430","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":24,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/430\/revisions"}],"predecessor-version":[{"id":3089,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/430\/revisions\/3089"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/parts\/621"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/430\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/media?parent=430"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapter-type?post=430"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/contributor?post=430"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/license?post=430"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}