{"id":4369,"date":"2022-04-09T15:30:49","date_gmt":"2022-04-09T15:30:49","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/?post_type=chapter&#038;p=4369"},"modified":"2022-04-10T01:58:56","modified_gmt":"2022-04-10T01:58:56","slug":"instructor-guide-2c-corequisite-support-2","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/chapter\/instructor-guide-2c-corequisite-support-2\/","title":{"raw":"Instructor Guide 1C: Forming Connections","rendered":"Instructor Guide 1C: Forming Connections"},"content":{"raw":"<h2>Overview<\/h2>\r\n<ul>\r\n \t<li>Students will learn how to identify observational units and variables in a dataset, how to organize data in a spreadsheet, and how to distinguish between categorical variables and quantitative variables. Students will understand that ethical issues are associated with the data collection and storage.<\/li>\r\n \t<li>Students work in pairs to consider what variables might be measured to address a new statistical question: Is there a relationship between a student's phone use in class and their grades?<\/li>\r\n \t<li>This activity connects back to the statistical problem-solving process introduced in\u00a0<em>Forming Connections [1A]<\/em>, prepares students for more advanced discussions of data collection and interrogation in\u00a0<em>Forming Connections [1D].<\/em><\/li>\r\n \t<li><span style=\"background-color: #ffff99;\">S1, S2, S3, C2, C3, C4, C6, V1, V4, O3 \u2190 Link to EBTP descriptions\u00a0<\/span><\/li>\r\n<\/ul>\r\n<h3>Prerequisite assumptions<\/h3>\r\nStudents should be able to do each of the following after completing the <em>What to Know<\/em> assignment.\r\n<ul>\r\n \t<li>Identify statistical investigative questions and\u00a0survey questions.<\/li>\r\n \t<li>Anticipate numerical and non-numerical responses to survey questions.<\/li>\r\n<\/ul>\r\n<h3>Intended goals for this activity<\/h3>\r\nAfter completing this activity, students should understand that there are multiple data collection and organization strategies that may be\u00a0considered for a single statistical question.. They should be able to\u00a0organize data in a spreadsheet, identify observational units and variables in a dataset, and classify variables as categorical or quantitative, and\u00a0quantitative variables as discrete or continuous.\r\n<h2>Synchronous Delivery and Activity Flow<\/h2>\r\nThe sample activity delivery below assumes a face-to-face class meeting but can be adapted to a fully online or hybrid delivery by using break-out rooms for pairs and small groups.\r\n<h3>Frame the activity (7 minutes)<\/h3>\r\n<ul>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Question 3 includes several survey questions. If you wish to collect data from the class to demonstrate storing it in a spreadsheet, take a few moments to have the students answer the questions. To save time, use a digital form to collect responses. It is reasonable, however, for students to analyze the questions in Question 3 without taking time to answer them.<\/li>\r\n \t<li aria-level=\"1\">This activity involves the relationship between the first two steps of the statistical problem-solving process students learned about in\u00a0<em>Forming Connections [1A] --\u00a0<\/em>how to get from a statistical investigative question to a data collection plan.<\/li>\r\n \t<li aria-level=\"1\">Have students answer Question 1 individually. <span style=\"background-color: #ffff99;\">O3<\/span><\/li>\r\n<\/ul>\r\n<h3>Activity Flow (18 minutes)<\/h3>\r\n<ul>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Question 2 -- working in pairs <span style=\"background-color: #ffff99;\">O3, C3, V1<\/span>\r\n<ul>\r\n \t<li aria-level=\"1\">Have students answer Question 2<\/li>\r\n \t<li aria-level=\"1\">Briefly discuss new vocabulary introduced: observational unit, variable, categorical,, quantitative, discrete, and continuous.<\/li>\r\n<\/ul>\r\n<\/li>\r\n \t<li aria-level=\"1\">Questions 3 - 6 -- working in groups of two or three <span style=\"background-color: #ffff99;\">V4, O3, C6<\/span>\r\n<ul>\r\n \t<li aria-level=\"1\">As students work, circulate through the room. Remind students who are stuck in Question 4 about the variety of questions presented in Question 3. Some characteristics can be defined as categorical or quantitative, depending on how the variables are defined. For example, do they want their variables to refer to a single class period or a student's ongoing habits?<\/li>\r\n \t<li aria-level=\"1\">If students finish early, ask which variables they starred. What advantages do these variables offer over the other options?<\/li>\r\n<\/ul>\r\n<\/li>\r\n<\/ul>\r\n<h3>Wrap-up\/transition (5 minutes)<\/h3>\r\n<ul>\r\n \t<li>Call on groups to share their ideas for measuring phone use (Question 4, Part A) and for measuring Grades (Question 4, Part B).<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Ask students to classify each variable as categorical or quantitative.<\/li>\r\n \t<li aria-level=\"1\">Ask students to name advantages\/disadvantages for each idea (statistically and practically)<\/li>\r\n \t<li aria-level=\"1\">Ask how the variables would change if class sections were treated as the observational units (Question 5).<\/li>\r\n \t<li aria-level=\"1\">Ask students if they have any ethical concerns about the data collection plans that have been proposed (Question 6). Connect concerns about privacy surrounding grades to the Family Educational Rights and Privacy Act (FERPA)[footnote]<a href=\"https:\/\/www2.ed.gov\/policy\/gen\/guid\/fpco\/ferpa\">https:\/\/www2.ed.gov\/policy\/gen\/guid\/fpco\/ferpa<\/a>[\/footnote].<\/li>\r\n \t<li aria-level=\"1\">Summarize: For any given statistical investigative question, there are multiple data collection and organization strategies that may be considered, each with its own set of advantages and disadvantages. It\u2019s important to recognize whether our variables are categorical or quantitative because this will affect all of our data analysis decisions in the next stage of the statistical process. It\u2019s also important to note the observational units because this will affect how the study results are interpreted in the final stage of the statistical process.<\/li>\r\n \t<li style=\"font-weight: 400;\" aria-level=\"1\">Assign the homework or\u00a0<em>Practice<\/em>\u00a0and any <em>What to Know<\/em> pages for the <em>Forming Connections<\/em> activities you plan to complete in the next class meeting. <span style=\"background-color: #ffff99;\">C2<\/span><\/li>\r\n<\/ul>","rendered":"<h2>Overview<\/h2>\n<ul>\n<li>Students will learn how to identify observational units and variables in a dataset, how to organize data in a spreadsheet, and how to distinguish between categorical variables and quantitative variables. Students will understand that ethical issues are associated with the data collection and storage.<\/li>\n<li>Students work in pairs to consider what variables might be measured to address a new statistical question: Is there a relationship between a student&#8217;s phone use in class and their grades?<\/li>\n<li>This activity connects back to the statistical problem-solving process introduced in\u00a0<em>Forming Connections [1A]<\/em>, prepares students for more advanced discussions of data collection and interrogation in\u00a0<em>Forming Connections [1D].<\/em><\/li>\n<li><span style=\"background-color: #ffff99;\">S1, S2, S3, C2, C3, C4, C6, V1, V4, O3 \u2190 Link to EBTP descriptions\u00a0<\/span><\/li>\n<\/ul>\n<h3>Prerequisite assumptions<\/h3>\n<p>Students should be able to do each of the following after completing the <em>What to Know<\/em> assignment.<\/p>\n<ul>\n<li>Identify statistical investigative questions and\u00a0survey questions.<\/li>\n<li>Anticipate numerical and non-numerical responses to survey questions.<\/li>\n<\/ul>\n<h3>Intended goals for this activity<\/h3>\n<p>After completing this activity, students should understand that there are multiple data collection and organization strategies that may be\u00a0considered for a single statistical question.. They should be able to\u00a0organize data in a spreadsheet, identify observational units and variables in a dataset, and classify variables as categorical or quantitative, and\u00a0quantitative variables as discrete or continuous.<\/p>\n<h2>Synchronous Delivery and Activity Flow<\/h2>\n<p>The sample activity delivery below assumes a face-to-face class meeting but can be adapted to a fully online or hybrid delivery by using break-out rooms for pairs and small groups.<\/p>\n<h3>Frame the activity (7 minutes)<\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Question 3 includes several survey questions. If you wish to collect data from the class to demonstrate storing it in a spreadsheet, take a few moments to have the students answer the questions. To save time, use a digital form to collect responses. It is reasonable, however, for students to analyze the questions in Question 3 without taking time to answer them.<\/li>\n<li aria-level=\"1\">This activity involves the relationship between the first two steps of the statistical problem-solving process students learned about in\u00a0<em>Forming Connections [1A] &#8212;\u00a0<\/em>how to get from a statistical investigative question to a data collection plan.<\/li>\n<li aria-level=\"1\">Have students answer Question 1 individually. <span style=\"background-color: #ffff99;\">O3<\/span><\/li>\n<\/ul>\n<h3>Activity Flow (18 minutes)<\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Question 2 &#8212; working in pairs <span style=\"background-color: #ffff99;\">O3, C3, V1<\/span>\n<ul>\n<li aria-level=\"1\">Have students answer Question 2<\/li>\n<li aria-level=\"1\">Briefly discuss new vocabulary introduced: observational unit, variable, categorical,, quantitative, discrete, and continuous.<\/li>\n<\/ul>\n<\/li>\n<li aria-level=\"1\">Questions 3 &#8211; 6 &#8212; working in groups of two or three <span style=\"background-color: #ffff99;\">V4, O3, C6<\/span>\n<ul>\n<li aria-level=\"1\">As students work, circulate through the room. Remind students who are stuck in Question 4 about the variety of questions presented in Question 3. Some characteristics can be defined as categorical or quantitative, depending on how the variables are defined. For example, do they want their variables to refer to a single class period or a student&#8217;s ongoing habits?<\/li>\n<li aria-level=\"1\">If students finish early, ask which variables they starred. What advantages do these variables offer over the other options?<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3>Wrap-up\/transition (5 minutes)<\/h3>\n<ul>\n<li>Call on groups to share their ideas for measuring phone use (Question 4, Part A) and for measuring Grades (Question 4, Part B).<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Ask students to classify each variable as categorical or quantitative.<\/li>\n<li aria-level=\"1\">Ask students to name advantages\/disadvantages for each idea (statistically and practically)<\/li>\n<li aria-level=\"1\">Ask how the variables would change if class sections were treated as the observational units (Question 5).<\/li>\n<li aria-level=\"1\">Ask students if they have any ethical concerns about the data collection plans that have been proposed (Question 6). Connect concerns about privacy surrounding grades to the Family Educational Rights and Privacy Act (FERPA)<a class=\"footnote\" title=\"https:\/\/www2.ed.gov\/policy\/gen\/guid\/fpco\/ferpa\" id=\"return-footnote-4369-1\" href=\"#footnote-4369-1\" aria-label=\"Footnote 1\"><sup class=\"footnote\">[1]<\/sup><\/a>.<\/li>\n<li aria-level=\"1\">Summarize: For any given statistical investigative question, there are multiple data collection and organization strategies that may be considered, each with its own set of advantages and disadvantages. It\u2019s important to recognize whether our variables are categorical or quantitative because this will affect all of our data analysis decisions in the next stage of the statistical process. It\u2019s also important to note the observational units because this will affect how the study results are interpreted in the final stage of the statistical process.<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\">Assign the homework or\u00a0<em>Practice<\/em>\u00a0and any <em>What to Know<\/em> pages for the <em>Forming Connections<\/em> activities you plan to complete in the next class meeting. <span style=\"background-color: #ffff99;\">C2<\/span><\/li>\n<\/ul>\n<hr class=\"before-footnotes clear\" \/><div class=\"footnotes\"><ol><li id=\"footnote-4369-1\"><a href=\"https:\/\/www2.ed.gov\/policy\/gen\/guid\/fpco\/ferpa\">https:\/\/www2.ed.gov\/policy\/gen\/guid\/fpco\/ferpa<\/a> <a href=\"#return-footnote-4369-1\" 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-4369","chapter","type-chapter","status-publish","hentry"],"part":4126,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/4369","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":7,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/4369\/revisions"}],"predecessor-version":[{"id":4440,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/4369\/revisions\/4440"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/parts\/4126"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/4369\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/media?parent=4369"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapter-type?post=4369"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/contributor?post=4369"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/license?post=4369"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}