{"id":275,"date":"2021-10-27T21:21:44","date_gmt":"2021-10-27T21:21:44","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/?post_type=chapter&#038;p=275"},"modified":"2022-02-18T16:23:05","modified_gmt":"2022-02-18T16:23:05","slug":"3a-forming-connections-with-categorical-variables","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/chapter\/3a-forming-connections-with-categorical-variables\/","title":{"raw":"Forming Connections in Displaying Categorical Data: 3A - 3","rendered":"Forming Connections in Displaying Categorical Data: 3A &#8211; 3"},"content":{"raw":"<div class=\"textbox learning-objectives\">\r\n<h3>objectives for this activity<\/h3>\r\nDuring this activity, you will:\r\n<ul>\r\n \t<li><a href=\"#Interpreting Categorical Variables\">Interpret which categorical variable is appropriate for answering a statistical question.<\/a><\/li>\r\n \t<li><a href=\"#Constructing Pie Charts\">Construct a pie chart from a frequency table of categorical data.<\/a><\/li>\r\n \t<li><a href=\"#Constructing Bar Graphs\">Construct a bar graph from a frequency table of categorical data.<\/a><\/li>\r\n \t<li><a href=\"#Data Distribution\">Use the displayed data distribution of categorical data to answer research questions.<\/a><\/li>\r\n<\/ul>\r\nClick on a skill above to jump to its location in this activity.\r\n\r\n<\/div>\r\n<h2>Larks or Owls?<\/h2>\r\n<span style=\"color: #000000;\"><strong><img class=\"aligncenter wp-image-1119 size-medium\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/5738\/2021\/10\/12005941\/3A-Sleep-300x201.jpeg\" alt=\"A student napping on a desk in a classroom\" width=\"300\" height=\"201\" \/><\/strong><\/span>\r\n\r\nIn a 2012 sleep study[footnote]\u00a0SleepStudy: Sleep Study. (2019, May 2). rdrr.oi. Retrieved from https:\/\/rdrr.io\/cran\/Lock5withR\/man\/SleepStudy.html[\/footnote], a sample of 253 college students completed skills tests to measure cognitive function, completed surveys that ask many questions about attitudes and habits, and kept sleep diaries to record time and quality of sleep over a two-week period. The relationship between sleep and academic performance was evaluated.\u00a0 During this activity, you'll use the Sleep Study dataset to see that there are multiple ways to display categorical data.\r\n<div>In the sleep study, students were asked if they identified as Larks, Owls, or Neither. A Lark is a morning person, an Owl is a night person, and Neither is a person who is neither a morning or night person.\u00a0Their responses were recorded in a variable named Chronotype.<\/div>\r\n<div><\/div>\r\n<div class=\"textbox tryit\">\r\n<h3>video placement<\/h3>\r\n<span style=\"background-color: #e6daf7;\">[Intro: \"In this activity, we'll use technology to create graphical displays of a categorical variable. You should be familiar with picking out the categorical data from a dataset and making a frequency table. Don't worry, we'll walk through the use of the analysis tool step by step. The key piece to take away from this activity will be understanding that there are multiple ways to display categorical data. You'll be able to create freqency tables, bar graphs, and pie charts using technology and then use data distributions displayed in those tables and graphs to answer questions about a variable. Before we get started, think about your own chronotype; are you an Owl, a Lark, or neither? How about the others who go to your school? Do you think college students tend to be one or the other?\"]<\/span>\r\n\r\n<\/div>\r\n<h2 id=\"Interpreting Categorical Variables\">Interpreting Categorical Variables<\/h2>\r\nBefore you look at the dataset, think for a moment about the assumptions you already hold about college students, then answer the first question below.\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 1<\/h3>\r\nWhat is your chronotype? Do you think college students are more likely to be larks, owls, or neither? Explain.\r\n\r\n[reveal-answer q=\"91518\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"91518\"]What do <em>you<\/em> think?[\/hidden-answer]\r\n\r\n<\/div>\r\nThe following 10 variables are included in the sleep study dataset. The variable names are presented in <em>italics<\/em> followed by a brief description. Recall that this is called a <em>data dictionary<\/em>.\r\n<ul>\r\n \t<li><em>Chronotype<\/em>: Lark, owl, or neither; a lark is a morning person, an owl is a night person, and neither is neither a morning nor a night person<\/li>\r\n \t<li><em>ClassYear<\/em>: 1, 2, 3, 4; 1 = freshman, 2 = sophomore, 3 = junior, 4 = senior<\/li>\r\n \t<li><em>NumEarlyClass<\/em>: Number of classes per week taken before 9 am<\/li>\r\n \t<li><em>EarlyClass<\/em>: 0, 1; 0 = is not taking any early classes and 1 = is taking at least one early class<\/li>\r\n \t<li><em>GPA<\/em>: Grade point average (0\u20134 scale)<\/li>\r\n \t<li><em>ClassesMissed<\/em>: Number of classes missed in a semester<\/li>\r\n \t<li><em>PoorSleepQuality<\/em>: Measure of sleep quality (higher values indicate poorer sleep)<\/li>\r\n \t<li><em>Stress<\/em>: Coded stress score, normal or high<\/li>\r\n \t<li><em>AlcoholUse<\/em>: Self-reported alcohol use\u2014abstain, light, moderate, heavy<\/li>\r\n \t<li><em>Drinks<\/em>: Number of alcoholic drinks per week<\/li>\r\n<\/ul>\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 2<\/h3>\r\n[ohm_question]240632[\/ohm_question]\r\n\r\n[reveal-answer q=\"78534\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"78534\"]Recall the definition of a categorical variable from the previous page.[\/hidden-answer]\r\n\r\n<\/div>\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 3<\/h3>\r\n[ohm_question]240633[\/ohm_question]\r\n\r\n[reveal-answer q=\"646305\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"646305\"]Which variable description best applies to answer this question?[\/hidden-answer]\r\n\r\n<\/div>\r\n<h2 id=\"Constructing Pie Charts\">Constructing Pie Charts<\/h2>\r\nLet\u2019s use technology to create a pie chart that visualizes the distribution of Chronotype for all 253 students in the study.\r\n<div class=\"textbox tryit\">\r\n<h3>video placement<\/h3>\r\n<span style=\"background-color: #e6daf7;\">[Guiding: \"This will be your first time using this tool in an activity. Let's see how it should look together. [display the tool, going through the steps below to create a pie chart.] ]<\/span>\r\n\r\n<\/div>\r\n<div class=\"textbox\">\r\n\r\nGo to the\u00a0<em>Describing and Exploring Categorical Data<\/em> tool at\u00a0<a href=\"https:\/\/dcmathpathways.shinyapps.io\/EDA_categorical\/\" target=\"_blank\" rel=\"noopener\">https:\/\/dcmathpathways.shinyapps.io\/EDA_categorical\/<\/a>\r\n<p style=\"padding-left: 30px;\">Step 1) Select the\u00a0<strong>One Categorical Variable<\/strong> tab.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 2)\u00a0Locate the dropdown under <strong>Enter Data<\/strong> and select <strong>From Textbook<\/strong>.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 3) Click on the dropdown menu for <strong>Dataset<\/strong> and choose <strong>Sleep Study \u2013 Lark vs. Owl<\/strong>.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 4) Scroll down to <strong>Additional Plots<\/strong> and select the <strong>Pie Chart<\/strong> option.\u00a0 The pie chart will appear below the bar graph.<\/p>\r\n\r\n<\/div>\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 4<\/h3>\r\nUse your pie chart to answer the question: \u201cAre college students likely to be morning people?\u201d Explain.\r\n\r\n[reveal-answer q=\"926672\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"926672\"]Be sure that you have selected the correct dataset: \"Sleep Study - Lark vs. Owl.\"[\/hidden-answer]\r\n\r\n<\/div>\r\nConsider a hypothetical class of 42 students, each of whom\u00a0answered the question, \"are you a lark, an owl, or neither?\" Let's suppose that 12 responded that they were larks, 20 that they were owls, and 10 said they were neither a lark nor an owl.\r\n<div class=\"textbox tryit\">\r\n<h3>video placement<\/h3>\r\n<span style=\"background-color: #e6daf7;\">[Guiding: \"[First demonstrate using fake information for a few observations (say, n = 5 or 6, for simplicity)to create a frequency table, then display the tool, going through the steps below to enter the data from the frequency table. Also show that students may, alternatively, enter the data as \"observations\" by making the appropriate selection under \"Enter Data\" and then entering observations as \"lark lark owl etc...] ]<\/span>\r\n\r\n<\/div>\r\nUse the <em><a href=\"https:\/\/dcmathpathways.shinyapps.io\/EDA_categorical\/\" target=\"_blank\" rel=\"noopener\">Describing and Exploring Categorical Data<\/a><\/em> tool to create a pie graph for these data. Follow these steps:\r\n<div class=\"textbox\">\r\n<p style=\"padding-left: 30px;\">Step 1) Select the <strong>One Categorical Variable<\/strong> tab.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 2)\u00a0Locate the dropdown under <strong>Enter Data<\/strong> and select <strong>Frequency Table.<\/strong><\/p>\r\n<p style=\"padding-left: 30px;\">Step 3) Enter \u201c3\u201d for <strong>Number of Categories.<\/strong><\/p>\r\n<p style=\"padding-left: 30px;\">Step 4) In the box under <strong>Name of Variable<\/strong>, type\u00a0Chronotype.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 5) Enter the labels for the 3 chronotypes and their respective numbers observed in the hypothetical class.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 6) Scroll down to locate\u00a0<strong>Additional Plots\u00a0<\/strong>and select <strong>Pie Chart<\/strong>.<\/p>\r\n\r\n<\/div>\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 5<\/h3>\r\n[ohm_question]240595[\/ohm_question]\r\n\r\n[reveal-answer q=\"242128\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"242128\"]Double-check the information you entered in the tool if your pie chart appears differently.[\/hidden-answer]\r\n\r\n<\/div>\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 6<\/h3>\r\nDo students in the hypothetical class tend to be owls or larks? How does the distribution of Chronotype for students in the survey compare to students in the hypothetical class?\r\n\r\n[reveal-answer q=\"239421\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"239421\"]Use the analysis you've done via the tool to answer this question.[\/hidden-answer]\r\n\r\n<\/div>\r\n<h2 id=\"Constructing Bar Graphs\">Constructing Bar Graphs<\/h2>\r\nLet's use a bar graph to examine another of the variables from the sleep study <em>Alcohol use<\/em>.\r\n<div class=\"textbox tryit\">\r\n<h3>video placement<\/h3>\r\n<span style=\"background-color: #e6daf7;\">[Guiding:\u00a0 [display the tool, going through the steps below to create a bar graph.] ]<\/span>\r\n\r\n<\/div>\r\nIn the <a href=\"https:\/\/dcmathpathways.shinyapps.io\/EDA_categorical\/\" target=\"_blank\" rel=\"noopener\"><em>Describing and Exploring Categorical Data<\/em><\/a> tool, follow these steps:\r\n<div class=\"textbox\">\r\n<p style=\"padding-left: 30px;\">Step 1)\u00a0Select the <strong>One Categorical Variable<\/strong> tab.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 2) Under <strong>Enter Data<\/strong> choose <strong>From Textbook<\/strong>.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 3) Under <strong>Dataset<\/strong>, select <strong>Sleep Study \u2013 Alcohol Use<\/strong>.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 4) Under <strong>Options<\/strong>, check the <strong>Customize Order<\/strong> box to change the order of the bars to provide more meaning.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 5) Click in the box under <strong>Choose Order of Categories<\/strong> and the order should be abstain, light, moderate, heavy.<\/p>\r\n<p style=\"padding-left: 30px;\">Step 6) Under\u00a0<strong>Additional Plots<\/strong> select None.<\/p>\r\n\r\n<\/div>\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 7<\/h3>\r\n[ohm_question]240597[\/ohm_question]\r\n\r\n[reveal-answer q=\"11007\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"11007\"]Double-check the information you entered in the tool if your pie chart appears differently.[\/hidden-answer]\r\n\r\n<\/div>\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 8<\/h3>\r\nHow do students classify their alcohol consumption?\r\n\r\n[reveal-answer q=\"965028\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"965028\"]Analyze the bar graph you created to answer this.[\/hidden-answer]\r\n\r\n<\/div>\r\n<h2 id=\"Data Distribution\">Data Distribution<\/h2>\r\nNow you try the tool on our own to create a graph. Use the dataset \u201cSleep Study \u2013 Class Year\u201d to create a bar graph to show the class years of the college students in the study. Make sure they are in the appropriate order. Look back to the steps above for guidance as needed.\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 9<\/h3>\r\nWrite a sentence explaining the bar graph you created from \"Sleep Study -- Class Year.\"\r\n\r\n[reveal-answer q=\"471883\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"471883\"]Compare the bars to one another. Do any of the class years seem to stand out in particular? About how many students from each class were in the study?[\/hidden-answer]\r\n\r\n<\/div>\r\n<div class=\"textbox key-takeaways\">\r\n<h3>question 10<\/h3>\r\nUse your previous answers to answer the question: \u201cIs there evidence of underage drinking at the college in this study?\u201d Include a few sentences to explain your reasoning and make sure to clarify which graphs you used to make this decision.\r\n\r\n[reveal-answer q=\"900443\"]Hint[\/reveal-answer]\r\n[hidden-answer a=\"900443\"]What do <em>you<\/em> think? What are the typical, traditional ages of college students in the class years? Be thorough in your answer. [\/hidden-answer]\r\n\r\n<\/div>\r\n<div class=\"textbox tryit\">\r\n<h3>video placement<\/h3>\r\n<span style=\"background-color: #e6daf7;\">[Wrap-up: \"What did you discover? Did you find evidence for underage drinking? We saw that there were many sophomores involved in the study and we saw that many students responded that they drank \"moderately.\" Do you feel the combination of these two variables points to underage drinking being present at the survey school? There are other good questions to ask about this data, as well. Do you think there would be a relationship between alcohol and academic performance? What about alcohol and sleep?\u00a0 Before we move on to the next section, let's recap the objectives for this activity. [voice over the list at the top of the page, or move through the page using jump links] You've identified the categorical variables in the dataset and used technology to create frequency tables, bar graphs, and pie charts, then used those displays to answer research questions about the data.\u00a0We'll return to this study in future sections of the course to investigate other questions: would owls drink more than larks? Are different class levels more likely to be larks or owls? These are all good questions. Can you think of others?\"]<\/span>\r\n\r\n<\/div>","rendered":"<div class=\"textbox learning-objectives\">\n<h3>objectives for this activity<\/h3>\n<p>During this activity, you will:<\/p>\n<ul>\n<li><a href=\"#Interpreting Categorical Variables\">Interpret which categorical variable is appropriate for answering a statistical question.<\/a><\/li>\n<li><a href=\"#Constructing Pie Charts\">Construct a pie chart from a frequency table of categorical data.<\/a><\/li>\n<li><a href=\"#Constructing Bar Graphs\">Construct a bar graph from a frequency table of categorical data.<\/a><\/li>\n<li><a href=\"#Data Distribution\">Use the displayed data distribution of categorical data to answer research questions.<\/a><\/li>\n<\/ul>\n<p>Click on a skill above to jump to its location in this activity.<\/p>\n<\/div>\n<h2>Larks or Owls?<\/h2>\n<p><span style=\"color: #000000;\"><strong><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-1119 size-medium\" src=\"https:\/\/s3-us-west-2.amazonaws.com\/courses-images\/wp-content\/uploads\/sites\/5738\/2021\/10\/12005941\/3A-Sleep-300x201.jpeg\" alt=\"A student napping on a desk in a classroom\" width=\"300\" height=\"201\" \/><\/strong><\/span><\/p>\n<p>In a 2012 sleep study<a class=\"footnote\" title=\"\u00a0SleepStudy: Sleep Study. (2019, May 2). rdrr.oi. Retrieved from https:\/\/rdrr.io\/cran\/Lock5withR\/man\/SleepStudy.html\" id=\"return-footnote-275-1\" href=\"#footnote-275-1\" aria-label=\"Footnote 1\"><sup class=\"footnote\">[1]<\/sup><\/a>, a sample of 253 college students completed skills tests to measure cognitive function, completed surveys that ask many questions about attitudes and habits, and kept sleep diaries to record time and quality of sleep over a two-week period. The relationship between sleep and academic performance was evaluated.\u00a0 During this activity, you&#8217;ll use the Sleep Study dataset to see that there are multiple ways to display categorical data.<\/p>\n<div>In the sleep study, students were asked if they identified as Larks, Owls, or Neither. A Lark is a morning person, an Owl is a night person, and Neither is a person who is neither a morning or night person.\u00a0Their responses were recorded in a variable named Chronotype.<\/div>\n<div><\/div>\n<div class=\"textbox tryit\">\n<h3>video placement<\/h3>\n<p><span style=\"background-color: #e6daf7;\">[Intro: &#8220;In this activity, we&#8217;ll use technology to create graphical displays of a categorical variable. You should be familiar with picking out the categorical data from a dataset and making a frequency table. Don&#8217;t worry, we&#8217;ll walk through the use of the analysis tool step by step. The key piece to take away from this activity will be understanding that there are multiple ways to display categorical data. You&#8217;ll be able to create freqency tables, bar graphs, and pie charts using technology and then use data distributions displayed in those tables and graphs to answer questions about a variable. Before we get started, think about your own chronotype; are you an Owl, a Lark, or neither? How about the others who go to your school? Do you think college students tend to be one or the other?&#8221;]<\/span><\/p>\n<\/div>\n<h2 id=\"Interpreting Categorical Variables\">Interpreting Categorical Variables<\/h2>\n<p>Before you look at the dataset, think for a moment about the assumptions you already hold about college students, then answer the first question below.<\/p>\n<div class=\"textbox key-takeaways\">\n<h3>question 1<\/h3>\n<p>What is your chronotype? Do you think college students are more likely to be larks, owls, or neither? Explain.<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q91518\">Hint<\/span><\/p>\n<div id=\"q91518\" class=\"hidden-answer\" style=\"display: none\">What do <em>you<\/em> think?<\/div>\n<\/div>\n<\/div>\n<p>The following 10 variables are included in the sleep study dataset. The variable names are presented in <em>italics<\/em> followed by a brief description. Recall that this is called a <em>data dictionary<\/em>.<\/p>\n<ul>\n<li><em>Chronotype<\/em>: Lark, owl, or neither; a lark is a morning person, an owl is a night person, and neither is neither a morning nor a night person<\/li>\n<li><em>ClassYear<\/em>: 1, 2, 3, 4; 1 = freshman, 2 = sophomore, 3 = junior, 4 = senior<\/li>\n<li><em>NumEarlyClass<\/em>: Number of classes per week taken before 9 am<\/li>\n<li><em>EarlyClass<\/em>: 0, 1; 0 = is not taking any early classes and 1 = is taking at least one early class<\/li>\n<li><em>GPA<\/em>: Grade point average (0\u20134 scale)<\/li>\n<li><em>ClassesMissed<\/em>: Number of classes missed in a semester<\/li>\n<li><em>PoorSleepQuality<\/em>: Measure of sleep quality (higher values indicate poorer sleep)<\/li>\n<li><em>Stress<\/em>: Coded stress score, normal or high<\/li>\n<li><em>AlcoholUse<\/em>: Self-reported alcohol use\u2014abstain, light, moderate, heavy<\/li>\n<li><em>Drinks<\/em>: Number of alcoholic drinks per week<\/li>\n<\/ul>\n<div class=\"textbox key-takeaways\">\n<h3>question 2<\/h3>\n<p><iframe loading=\"lazy\" id=\"ohm240632\" class=\"resizable\" src=\"https:\/\/ohm.lumenlearning.com\/multiembedq.php?id=240632&theme=oea&iframe_resize_id=ohm240632&show_question_numbers\" width=\"100%\" height=\"150\"><\/iframe><\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q78534\">Hint<\/span><\/p>\n<div id=\"q78534\" class=\"hidden-answer\" style=\"display: none\">Recall the definition of a categorical variable from the previous page.<\/div>\n<\/div>\n<\/div>\n<div class=\"textbox key-takeaways\">\n<h3>question 3<\/h3>\n<p><iframe loading=\"lazy\" id=\"ohm240633\" class=\"resizable\" src=\"https:\/\/ohm.lumenlearning.com\/multiembedq.php?id=240633&theme=oea&iframe_resize_id=ohm240633&show_question_numbers\" width=\"100%\" height=\"150\"><\/iframe><\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q646305\">Hint<\/span><\/p>\n<div id=\"q646305\" class=\"hidden-answer\" style=\"display: none\">Which variable description best applies to answer this question?<\/div>\n<\/div>\n<\/div>\n<h2 id=\"Constructing Pie Charts\">Constructing Pie Charts<\/h2>\n<p>Let\u2019s use technology to create a pie chart that visualizes the distribution of Chronotype for all 253 students in the study.<\/p>\n<div class=\"textbox tryit\">\n<h3>video placement<\/h3>\n<p><span style=\"background-color: #e6daf7;\">[Guiding: &#8220;This will be your first time using this tool in an activity. Let&#8217;s see how it should look together. [display the tool, going through the steps below to create a pie chart.] ]<\/span><\/p>\n<\/div>\n<div class=\"textbox\">\n<p>Go to the\u00a0<em>Describing and Exploring Categorical Data<\/em> tool at\u00a0<a href=\"https:\/\/dcmathpathways.shinyapps.io\/EDA_categorical\/\" target=\"_blank\" rel=\"noopener\">https:\/\/dcmathpathways.shinyapps.io\/EDA_categorical\/<\/a><\/p>\n<p style=\"padding-left: 30px;\">Step 1) Select the\u00a0<strong>One Categorical Variable<\/strong> tab.<\/p>\n<p style=\"padding-left: 30px;\">Step 2)\u00a0Locate the dropdown under <strong>Enter Data<\/strong> and select <strong>From Textbook<\/strong>.<\/p>\n<p style=\"padding-left: 30px;\">Step 3) Click on the dropdown menu for <strong>Dataset<\/strong> and choose <strong>Sleep Study \u2013 Lark vs. Owl<\/strong>.<\/p>\n<p style=\"padding-left: 30px;\">Step 4) Scroll down to <strong>Additional Plots<\/strong> and select the <strong>Pie Chart<\/strong> option.\u00a0 The pie chart will appear below the bar graph.<\/p>\n<\/div>\n<div class=\"textbox key-takeaways\">\n<h3>question 4<\/h3>\n<p>Use your pie chart to answer the question: \u201cAre college students likely to be morning people?\u201d Explain.<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q926672\">Hint<\/span><\/p>\n<div id=\"q926672\" class=\"hidden-answer\" style=\"display: none\">Be sure that you have selected the correct dataset: &#8220;Sleep Study &#8211; Lark vs. Owl.&#8221;<\/div>\n<\/div>\n<\/div>\n<p>Consider a hypothetical class of 42 students, each of whom\u00a0answered the question, &#8220;are you a lark, an owl, or neither?&#8221; Let&#8217;s suppose that 12 responded that they were larks, 20 that they were owls, and 10 said they were neither a lark nor an owl.<\/p>\n<div class=\"textbox tryit\">\n<h3>video placement<\/h3>\n<p><span style=\"background-color: #e6daf7;\">[Guiding: &#8220;[First demonstrate using fake information for a few observations (say, n = 5 or 6, for simplicity)to create a frequency table, then display the tool, going through the steps below to enter the data from the frequency table. Also show that students may, alternatively, enter the data as &#8220;observations&#8221; by making the appropriate selection under &#8220;Enter Data&#8221; and then entering observations as &#8220;lark lark owl etc&#8230;] ]<\/span><\/p>\n<\/div>\n<p>Use the <em><a href=\"https:\/\/dcmathpathways.shinyapps.io\/EDA_categorical\/\" target=\"_blank\" rel=\"noopener\">Describing and Exploring Categorical Data<\/a><\/em> tool to create a pie graph for these data. Follow these steps:<\/p>\n<div class=\"textbox\">\n<p style=\"padding-left: 30px;\">Step 1) Select the <strong>One Categorical Variable<\/strong> tab.<\/p>\n<p style=\"padding-left: 30px;\">Step 2)\u00a0Locate the dropdown under <strong>Enter Data<\/strong> and select <strong>Frequency Table.<\/strong><\/p>\n<p style=\"padding-left: 30px;\">Step 3) Enter \u201c3\u201d for <strong>Number of Categories.<\/strong><\/p>\n<p style=\"padding-left: 30px;\">Step 4) In the box under <strong>Name of Variable<\/strong>, type\u00a0Chronotype.<\/p>\n<p style=\"padding-left: 30px;\">Step 5) Enter the labels for the 3 chronotypes and their respective numbers observed in the hypothetical class.<\/p>\n<p style=\"padding-left: 30px;\">Step 6) Scroll down to locate\u00a0<strong>Additional Plots\u00a0<\/strong>and select <strong>Pie Chart<\/strong>.<\/p>\n<\/div>\n<div class=\"textbox key-takeaways\">\n<h3>question 5<\/h3>\n<p><iframe loading=\"lazy\" id=\"ohm240595\" class=\"resizable\" src=\"https:\/\/ohm.lumenlearning.com\/multiembedq.php?id=240595&theme=oea&iframe_resize_id=ohm240595&show_question_numbers\" width=\"100%\" height=\"150\"><\/iframe><\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q242128\">Hint<\/span><\/p>\n<div id=\"q242128\" class=\"hidden-answer\" style=\"display: none\">Double-check the information you entered in the tool if your pie chart appears differently.<\/div>\n<\/div>\n<\/div>\n<div class=\"textbox key-takeaways\">\n<h3>question 6<\/h3>\n<p>Do students in the hypothetical class tend to be owls or larks? How does the distribution of Chronotype for students in the survey compare to students in the hypothetical class?<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q239421\">Hint<\/span><\/p>\n<div id=\"q239421\" class=\"hidden-answer\" style=\"display: none\">Use the analysis you&#8217;ve done via the tool to answer this question.<\/div>\n<\/div>\n<\/div>\n<h2 id=\"Constructing Bar Graphs\">Constructing Bar Graphs<\/h2>\n<p>Let&#8217;s use a bar graph to examine another of the variables from the sleep study <em>Alcohol use<\/em>.<\/p>\n<div class=\"textbox tryit\">\n<h3>video placement<\/h3>\n<p><span style=\"background-color: #e6daf7;\">[Guiding:\u00a0 [display the tool, going through the steps below to create a bar graph.] ]<\/span><\/p>\n<\/div>\n<p>In the <a href=\"https:\/\/dcmathpathways.shinyapps.io\/EDA_categorical\/\" target=\"_blank\" rel=\"noopener\"><em>Describing and Exploring Categorical Data<\/em><\/a> tool, follow these steps:<\/p>\n<div class=\"textbox\">\n<p style=\"padding-left: 30px;\">Step 1)\u00a0Select the <strong>One Categorical Variable<\/strong> tab.<\/p>\n<p style=\"padding-left: 30px;\">Step 2) Under <strong>Enter Data<\/strong> choose <strong>From Textbook<\/strong>.<\/p>\n<p style=\"padding-left: 30px;\">Step 3) Under <strong>Dataset<\/strong>, select <strong>Sleep Study \u2013 Alcohol Use<\/strong>.<\/p>\n<p style=\"padding-left: 30px;\">Step 4) Under <strong>Options<\/strong>, check the <strong>Customize Order<\/strong> box to change the order of the bars to provide more meaning.<\/p>\n<p style=\"padding-left: 30px;\">Step 5) Click in the box under <strong>Choose Order of Categories<\/strong> and the order should be abstain, light, moderate, heavy.<\/p>\n<p style=\"padding-left: 30px;\">Step 6) Under\u00a0<strong>Additional Plots<\/strong> select None.<\/p>\n<\/div>\n<div class=\"textbox key-takeaways\">\n<h3>question 7<\/h3>\n<p><iframe loading=\"lazy\" id=\"ohm240597\" class=\"resizable\" src=\"https:\/\/ohm.lumenlearning.com\/multiembedq.php?id=240597&theme=oea&iframe_resize_id=ohm240597&show_question_numbers\" width=\"100%\" height=\"150\"><\/iframe><\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q11007\">Hint<\/span><\/p>\n<div id=\"q11007\" class=\"hidden-answer\" style=\"display: none\">Double-check the information you entered in the tool if your pie chart appears differently.<\/div>\n<\/div>\n<\/div>\n<div class=\"textbox key-takeaways\">\n<h3>question 8<\/h3>\n<p>How do students classify their alcohol consumption?<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q965028\">Hint<\/span><\/p>\n<div id=\"q965028\" class=\"hidden-answer\" style=\"display: none\">Analyze the bar graph you created to answer this.<\/div>\n<\/div>\n<\/div>\n<h2 id=\"Data Distribution\">Data Distribution<\/h2>\n<p>Now you try the tool on our own to create a graph. Use the dataset \u201cSleep Study \u2013 Class Year\u201d to create a bar graph to show the class years of the college students in the study. Make sure they are in the appropriate order. Look back to the steps above for guidance as needed.<\/p>\n<div class=\"textbox key-takeaways\">\n<h3>question 9<\/h3>\n<p>Write a sentence explaining the bar graph you created from &#8220;Sleep Study &#8212; Class Year.&#8221;<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q471883\">Hint<\/span><\/p>\n<div id=\"q471883\" class=\"hidden-answer\" style=\"display: none\">Compare the bars to one another. Do any of the class years seem to stand out in particular? About how many students from each class were in the study?<\/div>\n<\/div>\n<\/div>\n<div class=\"textbox key-takeaways\">\n<h3>question 10<\/h3>\n<p>Use your previous answers to answer the question: \u201cIs there evidence of underage drinking at the college in this study?\u201d Include a few sentences to explain your reasoning and make sure to clarify which graphs you used to make this decision.<\/p>\n<div class=\"qa-wrapper\" style=\"display: block\"><span class=\"show-answer collapsed\" style=\"cursor: pointer\" data-target=\"q900443\">Hint<\/span><\/p>\n<div id=\"q900443\" class=\"hidden-answer\" style=\"display: none\">What do <em>you<\/em> think? What are the typical, traditional ages of college students in the class years? Be thorough in your answer. <\/div>\n<\/div>\n<\/div>\n<div class=\"textbox tryit\">\n<h3>video placement<\/h3>\n<p><span style=\"background-color: #e6daf7;\">[Wrap-up: &#8220;What did you discover? Did you find evidence for underage drinking? We saw that there were many sophomores involved in the study and we saw that many students responded that they drank &#8220;moderately.&#8221; Do you feel the combination of these two variables points to underage drinking being present at the survey school? There are other good questions to ask about this data, as well. Do you think there would be a relationship between alcohol and academic performance? What about alcohol and sleep?\u00a0 Before we move on to the next section, let&#8217;s recap the objectives for this activity. [voice over the list at the top of the page, or move through the page using jump links] You&#8217;ve identified the categorical variables in the dataset and used technology to create frequency tables, bar graphs, and pie charts, then used those displays to answer research questions about the data.\u00a0We&#8217;ll return to this study in future sections of the course to investigate other questions: would owls drink more than larks? Are different class levels more likely to be larks or owls? These are all good questions. Can you think of others?&#8221;]<\/span><\/p>\n<\/div>\n<hr class=\"before-footnotes clear\" \/><div class=\"footnotes\"><ol><li id=\"footnote-275-1\">\u00a0SleepStudy: Sleep Study. (2019, May 2). rdrr.oi. Retrieved from https:\/\/rdrr.io\/cran\/Lock5withR\/man\/SleepStudy.html <a href=\"#return-footnote-275-1\" class=\"return-footnote\" aria-label=\"Return to footnote 1\">&crarr;<\/a><\/li><\/ol><\/div>","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-275","chapter","type-chapter","status-publish","hentry"],"part":3,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/275","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":52,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/275\/revisions"}],"predecessor-version":[{"id":3353,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/275\/revisions\/3353"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/parts\/3"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/275\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/media?parent=275"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapter-type?post=275"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/contributor?post=275"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/license?post=275"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}