{"id":5277,"date":"2022-08-19T14:30:16","date_gmt":"2022-08-19T14:30:16","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/?post_type=chapter&p=5277"},"modified":"2022-08-19T14:34:23","modified_gmt":"2022-08-19T14:34:23","slug":"10c-preview","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/chapter\/10c-preview\/","title":{"raw":"10C Preview","rendered":"10C Preview"},"content":{"raw":"Preparing for the next class\r\n\r\nIn the next in-class activity, you will need to understand how sample size affects margin of error and be able to determine the sample size needed to achieve a given margin of error when working with proportions.\r\n\r\nIn this preview assignment, you will be building on concepts you learned in In-Class Activities 10.A and 10.B. Refer to those activities if you need to review any vocabulary or skills.\r\nGo to https:\/\/dcmathpathways.shinyapps.io\/SampDist_prop\/ and open the DCMP Sampling Distribution of the Sample Proportion tool. Check the box for the option to enter numerical values for\u00a0[latex] n [\/latex] and\u00a0[latex] p [\/latex] and show summary statistics.\r\n
\r\n

Question 1<\/h3>\r\nSet the population proportion to 0.3. For each sample size in the table below, draw\u00a0 100 samples. Note the mean [latex] \\hat{p} [\/latex] and approximate minimum and maximum [latex] \\hat{p}[\/latex] generated for each sample size.\r\n
\r\n\r\n\r\n\r\n\r\n\r\n\r\n
Sample Size<\/td>\r\nMean [latex] \\hat{p} [\/latex]%<\/td>\r\nMinimum [latex] \\hat{p} [\/latex]%<\/td>\r\nMaximum [latex] \\hat{p} [\/latex]%<\/td>\r\n<\/tr>\r\n
50<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
100<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
500<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/div>\r\n \r\n\r\nHint: Use the summary statistics found at the bottom of the page. Use the \u201cSelect\u00a0 Range of x-axis (zoom in)\u201d feature to zoom in as needed.\r\n\r\n<\/div>\r\n
\r\n

Question 2<\/h3>\r\nWhich of the following statements best describes the changes you observed as the\u00a0 sample size increased?\r\n
    \r\n \t
  1. The mean [latex] \\hat{p} [\/latex]<\/li>\r\n \t
  2. The mean [latex] \\hat{p} [\/latex]<\/li>\r\n \t
  3. The interval between the minimum and maximum [latex] \\hat{p} [\/latex]<\/li>\r\n \t
  4. The interval between the minimum and maximum [latex] \\hat{p} [\/latex]<\/li>\r\n<\/ol>\r\nHint: Look at the difference between the minimum and maximum\u00a0[latex] \\hat{p} [\/latex]. Create additional tables if you need to see the changes again.\r\n\r\n<\/div>\r\nRecall that the equation for margin of error ([latex] E [\/latex]) is [latex] E = z^{*} \\bullet (standard~error) [\/latex] and the equation for standard error for a proportion is [latex] \\sqrt{\\frac{\\hat{p}(1-\\hat{p})}{n}} [\/latex], where [latex] \\hat{p} [\/latex] is the sample\u00a0\u00a0proportion and\u00a0[latex] n [\/latex] is the sample size.\r\n
    \r\n

    Question 3<\/h3>\r\nLook at the formula for margin of error. Which of the following statements best\u00a0 describes how you expect the margin of error ([latex] E [\/latex]) to change as the sample size ([latex] n [\/latex]) increases?\r\n
      \r\n \t
    1. The margin of error will increase.<\/li>\r\n \t
    2. The margin of error will decrease.<\/li>\r\n \t
    3. The margin of error will stay the same.<\/li>\r\n<\/ol>\r\nHint: What happens to the value of a fraction as the denominator increases?\r\n\r\n<\/div>\r\n
      \r\n

      Question 4<\/h3>\r\nNow, let\u2019s test your hypothesis.\r\n
        \r\n \t
      1. Go to https:\/\/dcmathpathways.shinyapps.io\/Inference_prop\/ to open the\u00a0 Inference for a Proportion tool. Change the \u201cEnter Data\u201d setting to \u201cNumber\u00a0 of Successes.\u201d Using a 95% confidence interval, use the tool to complete the\u00a0 table below.\r\n
        \r\n\r\n\r\n\r\n\r\n\r\n\r\n
        Sample Size<\/td>\r\n# of Successes<\/td>\r\nPoint Estimate<\/td>\r\nMargin of Error<\/td>\r\n<\/tr>\r\n
        100<\/td>\r\n30<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
        1,000<\/td>\r\n300<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n
        10,000<\/td>\r\n3,000<\/td>\r\n<\/td>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/div>\r\nHint: Enter the sample size and number of successes into the web tool.<\/li>\r\n \t
      2. Based on your findings, determine whether this statement is true or false:\r\nAs long as the point estimate and confidence level remain the same, the absolute value of margin of error will decrease as the sample size increases.<\/li>\r\n<\/ol>\r\n<\/div>\r\nIt is important to note that the formula [latex] E = z^{*} \\bullet (standard~error)[\/latex] is valid only if certain\u00a0 conditions are met:\r\n
          \r\n \t
        • Random sampling is used.<\/li>\r\n \t
        • The sample is less than 10% of the population.<\/li>\r\n<\/ul>\r\n\u2022 The sample is large enough that [latex] n\\hat{p} \\geq 10 [\/latex] and [latex] n(1-\\hat{p}) \\geq 10 [\/latex].\r\n
          \r\n

          Question 5<\/h3>\r\nFor each of the following combinations of [latex] n [\/latex] and [latex] \\hat{p} [\/latex], determine whether it would be\u00a0 appropriate to use the formula for the margin of error, [latex] E [\/latex]. Assume each sample is\u00a0 random and less than 10% of the population.\r\n
          \r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
          [latex]n [\/latex]<\/td>\r\n[latex] \\hat{p} [\/latex]%<\/td>\r\nAppropriate?\r\n\r\n(Yes or no)<\/td>\r\n<\/tr>\r\n
          50<\/td>\r\n0.1<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          100<\/td>\r\n0.1<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          45<\/td>\r\n0.5<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          30<\/td>\r\n0.5<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          25<\/td>\r\n0.9<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          120<\/td>\r\n0.9<\/td>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/div>\r\n \r\n\r\nHint: Are [latex] n\\hat{p} \\geq 10 [\/latex] and [latex] n(1-\\hat{p} \\geq 10 [\/latex]?\r\n\r\n<\/div>\r\nResearchers can use the same formula to determine the minimum sample size needed to produce a given margin of error simply by solving for [latex] n [\/latex]. The rearranged formula looks like this:\r\n\r\n[latex] n = \\hat{p}(1-\\hat{p})(\\frac{z^{*}}{E})^{2}[\/latex]\r\n\r\nNotice that this formula requires the researcher to know the value of [latex] \\hat{p} [\/latex], which is unknown. However, researchers often have preliminary data or prior research that can be used to estimate [latex] \\hat{p} [\/latex].\r\n\r\nIf there is no way to estimate [latex] \\hat{p} [\/latex], researchers will find the largest possible n by setting\u00a0[latex] \\hat{p} [\/latex] to 0.5. (Try it! The largest value you can get for [latex] \\hat{p}(1-\\hat{p})[\/latex]) is 0.25 when you set\u00a0[latex] \\hat{p} [\/latex] to 0.5.)\r\n
          \r\n

          Question 6<\/h3>\r\nGo to https:\/\/dcmathpathways.shinyapps.io\/Inference_prop\/ to open the DCMP\u00a0 Inference for a Proportion tool. At the top of the page, click \u201cFind Sample Size.\u201d Select \u201cUse Conservative Approach [latex] \\hat{p} [\/latex].\u201d\r\n\r\nWhat sample sizes would be needed for the following confidence level and margin of\u00a0 error combinations?\r\n
          \r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
          Confidence Level<\/td>\r\nMargin of Error<\/td>\r\nMinimum Sample\u00a0 Size<\/td>\r\n<\/tr>\r\n
          95%<\/td>\r\n[latex] \\pm [\/latex]2.5%<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          95%<\/td>\r\n[latex] \\pm [\/latex]4%<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          95%<\/td>\r\n[latex] \\pm [\/latex]6%<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          99%<\/td>\r\n[latex] \\pm [\/latex]6%<\/td>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\n<\/div>\r\nHint: Use the sliders to set the given values.\r\n\r\n<\/div>\r\n
          \r\n

          Question 7<\/h3>\r\nNow uncheck the \u201cUse Conservative Approach\u201d box. Use the same tool to calculate\u00a0 the necessary sample sizes for the following scenarios.\r\n
          \r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n
          Confidence Level<\/td>\r\nMargin of Error<\/td>\r\nPopulation\r\n\r\nProportion<\/td>\r\nMinimum Sample\u00a0 Size<\/td>\r\n<\/tr>\r\n
          95%<\/td>\r\n[latex] \\pm [\/latex]2.5%<\/td>\r\n0.1<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          95%<\/td>\r\n[latex] \\pm [\/latex]4%<\/td>\r\n0.2<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          95%<\/td>\r\n[latex] \\pm [\/latex]6%<\/td>\r\n0.3<\/td>\r\n<\/td>\r\n<\/tr>\r\n
          99%<\/td>\r\n[latex] \\pm [\/latex]6%<\/td>\r\n0.3<\/td>\r\n<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nHint: Use the sliders to set the given values.\r\n\r\n<\/div>\r\n<\/div>\r\nNotice that using the conservative [latex] \\hat{p} = 0.5 [\/latex] approach always yields a larger than\u00a0 necessary sample size.\r\n\r\nLooking Ahead\r\n\r\nChoose a context that is interesting to you, and bring the following information with you to class.\r\n
          \r\n

          Question 8<\/h3>\r\nWrite a question that can be answered using proportions.\r\n\r\nHint: Remember that percentages are ways to express information about\u00a0 proportions.\r\n\r\n<\/div>\r\n
          \r\n

          Question 9<\/h3>\r\nUse an Internet search to find an answer for your question. Note the source and any additional information provided regarding sample size, margin of error, or confidence level.\r\n\r\nHint: Ask a librarian if you need help with your Internet search.\r\n\r\n<\/div>\r\n ","rendered":"

          Preparing for the next class<\/p>\n

          In the next in-class activity, you will need to understand how sample size affects margin of error and be able to determine the sample size needed to achieve a given margin of error when working with proportions.<\/p>\n

          In this preview assignment, you will be building on concepts you learned in In-Class Activities 10.A and 10.B. Refer to those activities if you need to review any vocabulary or skills.
          \nGo to https:\/\/dcmathpathways.shinyapps.io\/SampDist_prop\/ and open the DCMP Sampling Distribution of the Sample Proportion tool. Check the box for the option to enter numerical values for\u00a0[latex]n[\/latex] and\u00a0[latex]p[\/latex] and show summary statistics.<\/p>\n

          \n

          Question 1<\/h3>\n

          Set the population proportion to 0.3. For each sample size in the table below, draw\u00a0 100 samples. Note the mean [latex]\\hat{p}[\/latex] and approximate minimum and maximum [latex]\\hat{p}[\/latex] generated for each sample size.<\/p>\n

          \n\n\n\n\n\n\n
          Sample Size<\/td>\nMean [latex]\\hat{p}[\/latex]%<\/td>\nMinimum [latex]\\hat{p}[\/latex]%<\/td>\nMaximum [latex]\\hat{p}[\/latex]%<\/td>\n<\/tr>\n
          50<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
          100<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
          500<\/td>\n<\/td>\n<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

           <\/p>\n

          Hint: Use the summary statistics found at the bottom of the page. Use the \u201cSelect\u00a0 Range of x-axis (zoom in)\u201d feature to zoom in as needed.<\/p>\n<\/div>\n

          \n

          Question 2<\/h3>\n

          Which of the following statements best describes the changes you observed as the\u00a0 sample size increased?<\/p>\n

            \n
          1. The mean [latex]\\hat{p}[\/latex]<\/li>\n
          2. The mean [latex]\\hat{p}[\/latex]<\/li>\n
          3. The interval between the minimum and maximum [latex]\\hat{p}[\/latex]<\/li>\n
          4. The interval between the minimum and maximum [latex]\\hat{p}[\/latex]<\/li>\n<\/ol>\n

            Hint: Look at the difference between the minimum and maximum\u00a0[latex]\\hat{p}[\/latex]. Create additional tables if you need to see the changes again.<\/p>\n<\/div>\n

            Recall that the equation for margin of error ([latex]E[\/latex]) is [latex]E = z^{*} \\bullet (standard~error)[\/latex] and the equation for standard error for a proportion is [latex]\\sqrt{\\frac{\\hat{p}(1-\\hat{p})}{n}}[\/latex], where [latex]\\hat{p}[\/latex] is the sample\u00a0\u00a0proportion and\u00a0[latex]n[\/latex] is the sample size.<\/p>\n

            \n

            Question 3<\/h3>\n

            Look at the formula for margin of error. Which of the following statements best\u00a0 describes how you expect the margin of error ([latex]E[\/latex]) to change as the sample size ([latex]n[\/latex]) increases?<\/p>\n

              \n
            1. The margin of error will increase.<\/li>\n
            2. The margin of error will decrease.<\/li>\n
            3. The margin of error will stay the same.<\/li>\n<\/ol>\n

              Hint: What happens to the value of a fraction as the denominator increases?<\/p>\n<\/div>\n

              \n

              Question 4<\/h3>\n

              Now, let\u2019s test your hypothesis.<\/p>\n

                \n
              1. Go to https:\/\/dcmathpathways.shinyapps.io\/Inference_prop\/ to open the\u00a0 Inference for a Proportion tool. Change the \u201cEnter Data\u201d setting to \u201cNumber\u00a0 of Successes.\u201d Using a 95% confidence interval, use the tool to complete the\u00a0 table below.\n
                \n\n\n\n\n\n\n
                Sample Size<\/td>\n# of Successes<\/td>\nPoint Estimate<\/td>\nMargin of Error<\/td>\n<\/tr>\n
                100<\/td>\n30<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
                1,000<\/td>\n300<\/td>\n<\/td>\n<\/td>\n<\/tr>\n
                10,000<\/td>\n3,000<\/td>\n<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

                Hint: Enter the sample size and number of successes into the web tool.<\/li>\n

              2. Based on your findings, determine whether this statement is true or false:
                \nAs long as the point estimate and confidence level remain the same, the absolute value of margin of error will decrease as the sample size increases.<\/li>\n<\/ol>\n<\/div>\n

                It is important to note that the formula [latex]E = z^{*} \\bullet (standard~error)[\/latex] is valid only if certain\u00a0 conditions are met:<\/p>\n

                  \n
                • Random sampling is used.<\/li>\n
                • The sample is less than 10% of the population.<\/li>\n<\/ul>\n

                  \u2022 The sample is large enough that [latex]n\\hat{p} \\geq 10[\/latex] and [latex]n(1-\\hat{p}) \\geq 10[\/latex].<\/p>\n

                  \n

                  Question 5<\/h3>\n

                  For each of the following combinations of [latex]n[\/latex] and [latex]\\hat{p}[\/latex], determine whether it would be\u00a0 appropriate to use the formula for the margin of error, [latex]E[\/latex]. Assume each sample is\u00a0 random and less than 10% of the population.<\/p>\n

                  \n\n\n\n\n\n\n\n\n\n
                  [latex]n[\/latex]<\/td>\n[latex]\\hat{p}[\/latex]%<\/td>\nAppropriate?<\/p>\n

                  (Yes or no)<\/td>\n<\/tr>\n

                  50<\/td>\n0.1<\/td>\n<\/td>\n<\/tr>\n
                  100<\/td>\n0.1<\/td>\n<\/td>\n<\/tr>\n
                  45<\/td>\n0.5<\/td>\n<\/td>\n<\/tr>\n
                  30<\/td>\n0.5<\/td>\n<\/td>\n<\/tr>\n
                  25<\/td>\n0.9<\/td>\n<\/td>\n<\/tr>\n
                  120<\/td>\n0.9<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

                   <\/p>\n

                  Hint: Are [latex]n\\hat{p} \\geq 10[\/latex] and [latex]n(1-\\hat{p} \\geq 10[\/latex]?<\/p>\n<\/div>\n

                  Researchers can use the same formula to determine the minimum sample size needed to produce a given margin of error simply by solving for [latex]n[\/latex]. The rearranged formula looks like this:<\/p>\n

                  [latex]n = \\hat{p}(1-\\hat{p})(\\frac{z^{*}}{E})^{2}[\/latex]<\/p>\n

                  Notice that this formula requires the researcher to know the value of [latex]\\hat{p}[\/latex], which is unknown. However, researchers often have preliminary data or prior research that can be used to estimate [latex]\\hat{p}[\/latex].<\/p>\n

                  If there is no way to estimate [latex]\\hat{p}[\/latex], researchers will find the largest possible n by setting\u00a0[latex]\\hat{p}[\/latex] to 0.5. (Try it! The largest value you can get for [latex]\\hat{p}(1-\\hat{p})[\/latex]) is 0.25 when you set\u00a0[latex]\\hat{p}[\/latex] to 0.5.)<\/p>\n

                  \n

                  Question 6<\/h3>\n

                  Go to https:\/\/dcmathpathways.shinyapps.io\/Inference_prop\/ to open the DCMP\u00a0 Inference for a Proportion tool. At the top of the page, click \u201cFind Sample Size.\u201d Select \u201cUse Conservative Approach [latex]\\hat{p}[\/latex].\u201d<\/p>\n

                  What sample sizes would be needed for the following confidence level and margin of\u00a0 error combinations?<\/p>\n

                  \n\n\n\n\n\n\n\n
                  Confidence Level<\/td>\nMargin of Error<\/td>\nMinimum Sample\u00a0 Size<\/td>\n<\/tr>\n
                  95%<\/td>\n[latex]\\pm[\/latex]2.5%<\/td>\n<\/td>\n<\/tr>\n
                  95%<\/td>\n[latex]\\pm[\/latex]4%<\/td>\n<\/td>\n<\/tr>\n
                  95%<\/td>\n[latex]\\pm[\/latex]6%<\/td>\n<\/td>\n<\/tr>\n
                  99%<\/td>\n[latex]\\pm[\/latex]6%<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

                  Hint: Use the sliders to set the given values.<\/p>\n<\/div>\n

                  \n

                  Question 7<\/h3>\n

                  Now uncheck the \u201cUse Conservative Approach\u201d box. Use the same tool to calculate\u00a0 the necessary sample sizes for the following scenarios.<\/p>\n

                  \n\n\n\n\n\n\n\n
                  Confidence Level<\/td>\nMargin of Error<\/td>\nPopulation<\/p>\n

                  Proportion<\/td>\n

                  		Minimum Sample\u00a0 Size<\/td>\n<\/tr>\n
                  95%<\/td>\n[latex]\\pm[\/latex]2.5%<\/td>\n0.1<\/td>\n<\/td>\n<\/tr>\n
                  95%<\/td>\n[latex]\\pm[\/latex]4%<\/td>\n0.2<\/td>\n<\/td>\n<\/tr>\n
                  95%<\/td>\n[latex]\\pm[\/latex]6%<\/td>\n0.3<\/td>\n<\/td>\n<\/tr>\n
                  99%<\/td>\n[latex]\\pm[\/latex]6%<\/td>\n0.3<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                  Hint: Use the sliders to set the given values.<\/p>\n<\/div>\n<\/div>\n

                  Notice that using the conservative [latex]\\hat{p} = 0.5[\/latex] approach always yields a larger than\u00a0 necessary sample size.<\/p>\n

                  Looking Ahead<\/p>\n

                  Choose a context that is interesting to you, and bring the following information with you to class.<\/p>\n

                  \n

                  Question 8<\/h3>\n

                  Write a question that can be answered using proportions.<\/p>\n

                  Hint: Remember that percentages are ways to express information about\u00a0 proportions.<\/p>\n<\/div>\n

                  \n

                  Question 9<\/h3>\n

                  Use an Internet search to find an answer for your question. Note the source and any additional information provided regarding sample size, margin of error, or confidence level.<\/p>\n

                  Hint: Ask a librarian if you need help with your Internet search.<\/p>\n<\/div>\n

                   <\/p>\n","protected":false},"author":574340,"menu_order":9,"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-5277","chapter","type-chapter","status-publish","hentry"],"part":5220,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/5277","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\/574340"}],"version-history":[{"count":6,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/5277\/revisions"}],"predecessor-version":[{"id":5686,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/5277\/revisions\/5686"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/parts\/5220"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapters\/5277\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/media?parent=5277"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/pressbooks\/v2\/chapter-type?post=5277"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/contributor?post=5277"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/lumen-danacenter-statsmockup\/wp-json\/wp\/v2\/license?post=5277"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}