{"id":264,"date":"2016-04-21T22:43:41","date_gmt":"2016-04-21T22:43:41","guid":{"rendered":"https:\/\/courses.lumenlearning.com\/introstats1xmaster\/?post_type=chapter&#038;p=264"},"modified":"2021-07-04T15:37:32","modified_gmt":"2021-07-04T15:37:32","slug":"answers-to-selected-exercises-9","status":"publish","type":"chapter","link":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/chapter\/answers-to-selected-exercises-9\/","title":{"raw":"Answers to Selected Exercises","rendered":"Answers to Selected Exercises"},"content":{"raw":"1. AIDS patients.\r\n\r\n3. The average length of time (in months) AIDS patients live after treatment.\r\n\r\n5. [latex]X[\/latex] = the length of time (in months) AIDS patients live after treatment\r\n\r\n7.\r\n<ol id=\"element-36236\" data-mark-suffix=\".\" data-number-style=\"lower-alpha\">\r\n \t<li data-mark-suffix=\".\">all children who take ski or snowboard lessons<\/li>\r\n \t<li data-mark-suffix=\".\">a group of these children<\/li>\r\n \t<li data-mark-suffix=\".\">the population mean age of children who take their first snowboard lesson<\/li>\r\n \t<li data-mark-suffix=\".\">the sample mean age of children who take their first snowboard lesson<\/li>\r\n \t<li data-mark-suffix=\".\">[latex]X[\/latex] = the age of one child who takes his or her first ski or snowboard lesson<\/li>\r\n \t<li data-mark-suffix=\".\">values for [latex]X[\/latex], such as [latex]3[\/latex], [latex]7[\/latex], and so on<\/li>\r\n<\/ol>\r\n9.\r\n<ol id=\"element-362362\" data-mark-suffix=\".\" data-number-style=\"lower-alpha\">\r\n \t<li data-mark-suffix=\".\">the clients of the insurance companies<\/li>\r\n \t<li data-mark-suffix=\".\">a group of the clients<\/li>\r\n \t<li data-mark-suffix=\".\">the mean health costs of the clients<\/li>\r\n \t<li data-mark-suffix=\".\">the mean health costs of the sample<\/li>\r\n \t<li data-mark-suffix=\".\">[latex]X[\/latex] = the health costs of one client<\/li>\r\n \t<li data-mark-suffix=\".\">values for [latex]X[\/latex], such as [latex]34[\/latex], [latex]9[\/latex], [latex]82[\/latex], and so on<\/li>\r\n<\/ol>\r\n11.\r\n<ol id=\"element-362363\" data-mark-suffix=\".\" data-number-style=\"lower-alpha\">\r\n \t<li data-mark-suffix=\".\">all the clients of this counselor<\/li>\r\n \t<li data-mark-suffix=\".\">a group of clients of this marriage counselor<\/li>\r\n \t<li data-mark-suffix=\".\">the proportion of all her clients who stay married<\/li>\r\n \t<li data-mark-suffix=\".\">the proportion of the sample of the counselor\u2019s clients who stay married<\/li>\r\n \t<li data-mark-suffix=\".\">[latex]X[\/latex] = the number of couples who stay married<\/li>\r\n \t<li data-mark-suffix=\".\">yes, no<\/li>\r\n<\/ol>\r\n13.\r\n<ol id=\"element-362356\" data-mark-suffix=\".\" data-number-style=\"lower-alpha\">\r\n \t<li data-mark-suffix=\".\">all people (maybe in a certain geographic area, such as the United States)<\/li>\r\n \t<li data-mark-suffix=\".\">a group of the people<\/li>\r\n \t<li data-mark-suffix=\".\">the proportion of all people who will buy the product<\/li>\r\n \t<li data-mark-suffix=\".\">the proportion of the sample who will buy the product<\/li>\r\n \t<li data-mark-suffix=\".\">[latex]X[\/latex] = the number of people who will buy it<\/li>\r\n \t<li data-mark-suffix=\".\">buy, not buy<\/li>\r\n<\/ol>\r\n15. a\r\n\r\n17. b\r\n\r\n19. a\r\n\r\n21.\r\n<ol id=\"fs-idm80641104\" data-number-style=\"lower-alpha\">\r\n \t<li>[latex]0.5242[\/latex]<\/li>\r\n \t<li>[latex]0.03[\/latex]%<\/li>\r\n \t<li>[latex]6.86[\/latex]%<\/li>\r\n \t<li>[latex]\\frac{823,088}{823,856}[\/latex]<\/li>\r\n \t<li>quantitative discrete<\/li>\r\n \t<li>quantitative continuous<\/li>\r\n \t<li>In both years, underwater earthquakes produced massive tsunamis.<\/li>\r\n<\/ol>\r\n23. cluster\r\n\r\n25. convenience\r\n\r\n27.\u00a0values for [latex]X[\/latex], such as [latex]3[\/latex], [latex]4[\/latex], [latex]11[\/latex], and so on\r\n\r\n29.\u00a0No, we do not have enough information to make such a claim.\r\n\r\n31.\u00a0Take a simple random sample from each group. One way is by assigning a number to each patient and using a random number generator to randomly select patients.\r\n\r\n33.\u00a0This would be convenience sampling and is not random.\r\n\r\n35.\u00a0Yes, the sample size of [latex]150[\/latex] would be large enough to reflect a population of one school.\r\n\r\n37.\u00a0Even though the specific data support each researcher\u2019s conclusions, the different results suggest that more data need to be collected before the researchers can reach a conclusion.\r\n\r\n39.\u00a0There is not enough information given to judge if either one is correct or incorrect.\r\n\r\n41.\u00a0The software program seems to work because the second study shows that more patients improve while using the software than not. Even though the difference is not as large as that in the first study, the results from the second study are likely more reliable and still show improvement.\r\n\r\n43.\u00a0Yes, because we cannot tell if the improvement was due to the software or the exercise; the data is confounded, and a reliable conclusion cannot be drawn. New studies should be performed.\r\n\r\n45.\u00a0No, even though the sample is large enough, the fact that the sample consists of volunteers makes it a self-selected sample, which is not reliable.\r\n\r\n47.\u00a0No, even though the sample is a large portion of the population, two responses are not enough to justify any conclusions. Because the population is so small, it would be better to include everyone in the population to get the most accurate data.\r\n\r\n49.\u00a0quantitative discrete, [latex]150[\/latex]\r\n\r\n51.\u00a0qualitative, Oakland A\u2019s\r\n\r\n53.\u00a0quantitative discrete, [latex]11,234[\/latex] students\r\n\r\n55.\u00a0qualitative, Crest\r\n\r\n57.\u00a0quantitative continuous, [latex]47.3[\/latex] years\r\n\r\n59. b\r\n\r\n61.\r\n<ol id=\"eip-idm59103408\" data-number-style=\"lower-alpha\">\r\n \t<li>The survey was conducted using six similar flights.\r\n<div data-type=\"newline\"><\/div>\r\nThe survey would not be a true representation of the entire population of air travelers.\r\n<div data-type=\"newline\"><\/div>\r\nConducting the survey on a holiday weekend will not produce representative results.<\/li>\r\n \t<li>Conduct the survey during different times of the year.\r\n<div data-type=\"newline\"><\/div>\r\nConduct the survey using flights to and from various locations.\r\n<div data-type=\"newline\"><\/div>\r\nConduct the survey on different days of the week.<\/li>\r\n<\/ol>\r\n63.\u00a0Answers will vary. Sample Answer: You could use a systematic sampling method. Stop the tenth person as they leave one of the buildings on campus at 9:50 in the morning. Then stop the tenth person as they leave a different building on campus at 1:50 in the afternoon.\r\n\r\n65.\u00a0Answers will vary. Sample Answer: Many people will not respond to mail surveys. If they do respond to the surveys, you can\u2019t be sure who is responding. In addition, mailing lists can be incomplete.\r\n\r\n67. b\r\n\r\n69.\u00a0convenience cluster stratified systematic simple random\r\n\r\n71.\r\n<ol id=\"eip-idp50853056\" data-mark-suffix=\".\" data-number-style=\"lower-alpha\">\r\n \t<li data-mark-suffix=\".\">qualitative<\/li>\r\n \t<li data-mark-suffix=\".\">quantitative discrete<\/li>\r\n \t<li data-mark-suffix=\".\">quantitative discrete<\/li>\r\n \t<li data-mark-suffix=\".\">qualitative<\/li>\r\n<\/ol>\r\n73.\u00a0Causality: The fact that two variables are related does not guarantee that one variable is influencing the other. We cannot assume that crime rate impacts education level or that education level impacts crime rate.\r\n\r\nConfounding: There are many factors that define a community other than education level and crime rate. Communities with high crime rates and high education levels may have other lurking variables that distinguish them from communities with lower crime rates and lower education levels. Because we cannot isolate these variables of interest, we cannot draw valid conclusions about the connection between education and crime. Possible lurking variables include police expenditures, unemployment levels, region, average age, and size.\r\n\r\n75.\r\n<ol id=\"fs-idm70068752\" data-number-style=\"lower-alpha\">\r\n \t<li>Possible reasons: increased use of caller id, decreased use of landlines, increased use of private numbers, voice mail, privacy managers, hectic nature of personal schedules, decreased willingness to be interviewed<\/li>\r\n \t<li>When a large number of people refuse to participate, then the sample may not have the same characteristics of the population. Perhaps the majority of people willing to participate are doing so because they feel strongly about the subject of the survey.<\/li>\r\n<\/ol>\r\n77.\r\n<ol id=\"eip-idm34826016\" data-element-type=\"enumerated\" data-number-style=\"lower-alpha\">\r\n \t<li>ordinal<\/li>\r\n \t<li>interval<\/li>\r\n \t<li>nominal<\/li>\r\n \t<li>nominal<\/li>\r\n \t<li>ratio<\/li>\r\n \t<li>ordinal<\/li>\r\n \t<li>nominal<\/li>\r\n \t<li>interval<\/li>\r\n \t<li>ratio<\/li>\r\n \t<li>interval<\/li>\r\n \t<li>ratio<\/li>\r\n \t<li>ordinal<\/li>\r\n<\/ol>\r\n79.\r\n<table id=\"eip-93\" summary=\"Filled Flossing Frequency for Adults with Gum Disease\">\r\n<thead>\r\n<tr>\r\n<th># Flossing per Week<\/th>\r\n<th>Frequency<\/th>\r\n<th>Relative Frequency<\/th>\r\n<th>Cumulative Relative Frequency<\/th>\r\n<\/tr>\r\n<\/thead>\r\n<tbody>\r\n<tr>\r\n<td>[latex]0[\/latex]<\/td>\r\n<td>[latex]27[\/latex]<\/td>\r\n<td>[latex]0.4500[\/latex]<\/td>\r\n<td>[latex]0.4500[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>[latex]1[\/latex]<\/td>\r\n<td>[latex]18[\/latex]<\/td>\r\n<td>[latex]0.3000[\/latex]<\/td>\r\n<td>[latex]0.7500[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>[latex]3[\/latex]<\/td>\r\n<td>[latex]11[\/latex]<\/td>\r\n<td>[latex]0.1833[\/latex]<\/td>\r\n<td>[latex]0.9333[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>[latex]6[\/latex]<\/td>\r\n<td>[latex]3[\/latex]<\/td>\r\n<td>[latex]0.0500[\/latex]<\/td>\r\n<td>[latex]0.9833[\/latex]<\/td>\r\n<\/tr>\r\n<tr>\r\n<td>[latex]7[\/latex]<\/td>\r\n<td>[latex]1[\/latex]<\/td>\r\n<td>[latex]0.0167[\/latex]<\/td>\r\n<td>[latex]1[\/latex]<\/td>\r\n<\/tr>\r\n<\/tbody>\r\n<\/table>\r\nb. [latex]5.00[\/latex]%\r\nc. [latex]93.33[\/latex]%\r\n\r\n81.\u00a0The sum of the travel times is [latex]1,173.1[\/latex]. Divide the sum by [latex]50[\/latex] to calculate the mean value: [latex]23.462[\/latex]. Because each state\u2019s travel time was measured to the nearest tenth, round this calculation to the nearest hundredth: [latex]23.46[\/latex].\r\n\r\n83. b\r\n\r\n85.\r\n<ol id=\"eip-idm79742704\" data-number-style=\"lower-alpha\">\r\n \t<li>Inmates may not feel comfortable refusing participation, or may feel obligated to take advantage of the promised benefits. They may not feel truly free to refuse participation.<\/li>\r\n \t<li>Parents can provide consent on behalf of their children, but children are not competent to provide consent for themselves.<\/li>\r\n \t<li>All risks and benefits must be clearly outlined. Study participants must be informed of relevant aspects of the study in order to give appropriate consent.<\/li>\r\n<\/ol>\r\n87.\r\nExplanatory variable: amount of sleep\r\n<div data-type=\"newline\" data-count=\"1\"><\/div>\r\nResponse variable: performance measured in assigned tasks\r\n<div data-type=\"newline\" data-count=\"1\"><\/div>\r\nTreatments: normal sleep and [latex]27[\/latex] hours of total sleep deprivation\r\n<div data-type=\"newline\" data-count=\"1\"><\/div>\r\nExperimental Units: [latex]19[\/latex] professional drivers\r\n<div data-type=\"newline\" data-count=\"1\"><\/div>\r\nLurking variables: none \u2013 all drivers participated in both treatments\r\n<div data-type=\"newline\" data-count=\"1\"><\/div>\r\nRandom assignment: treatments were assigned in random order; this eliminated the effect of any \u201clearning\u201d that may take place during the first experimental session\r\n<div data-type=\"newline\" data-count=\"1\"><\/div>\r\nControl\/Placebo: completing the experimental session under normal sleep conditions\r\n<div data-type=\"newline\" data-count=\"1\"><\/div>\r\nBlinding: researchers evaluating subjects\u2019 performance must not know which treatment is being applied at the time\r\n\r\n89.\u00a0You cannot assume that the numbers of complaints reflect the quality of the airlines. The airlines shown with the greatest number of complaints are the ones with the most passengers. You must consider the appropriateness of methods for presenting data; in this case displaying totals is misleading","rendered":"<p>1. AIDS patients.<\/p>\n<p>3. The average length of time (in months) AIDS patients live after treatment.<\/p>\n<p>5. [latex]X[\/latex] = the length of time (in months) AIDS patients live after treatment<\/p>\n<p>7.<\/p>\n<ol id=\"element-36236\" data-mark-suffix=\".\" data-number-style=\"lower-alpha\">\n<li data-mark-suffix=\".\">all children who take ski or snowboard lessons<\/li>\n<li data-mark-suffix=\".\">a group of these children<\/li>\n<li data-mark-suffix=\".\">the population mean age of children who take their first snowboard lesson<\/li>\n<li data-mark-suffix=\".\">the sample mean age of children who take their first snowboard lesson<\/li>\n<li data-mark-suffix=\".\">[latex]X[\/latex] = the age of one child who takes his or her first ski or snowboard lesson<\/li>\n<li data-mark-suffix=\".\">values for [latex]X[\/latex], such as [latex]3[\/latex], [latex]7[\/latex], and so on<\/li>\n<\/ol>\n<p>9.<\/p>\n<ol id=\"element-362362\" data-mark-suffix=\".\" data-number-style=\"lower-alpha\">\n<li data-mark-suffix=\".\">the clients of the insurance companies<\/li>\n<li data-mark-suffix=\".\">a group of the clients<\/li>\n<li data-mark-suffix=\".\">the mean health costs of the clients<\/li>\n<li data-mark-suffix=\".\">the mean health costs of the sample<\/li>\n<li data-mark-suffix=\".\">[latex]X[\/latex] = the health costs of one client<\/li>\n<li data-mark-suffix=\".\">values for [latex]X[\/latex], such as [latex]34[\/latex], [latex]9[\/latex], [latex]82[\/latex], and so on<\/li>\n<\/ol>\n<p>11.<\/p>\n<ol id=\"element-362363\" data-mark-suffix=\".\" data-number-style=\"lower-alpha\">\n<li data-mark-suffix=\".\">all the clients of this counselor<\/li>\n<li data-mark-suffix=\".\">a group of clients of this marriage counselor<\/li>\n<li data-mark-suffix=\".\">the proportion of all her clients who stay married<\/li>\n<li data-mark-suffix=\".\">the proportion of the sample of the counselor\u2019s clients who stay married<\/li>\n<li data-mark-suffix=\".\">[latex]X[\/latex] = the number of couples who stay married<\/li>\n<li data-mark-suffix=\".\">yes, no<\/li>\n<\/ol>\n<p>13.<\/p>\n<ol id=\"element-362356\" data-mark-suffix=\".\" data-number-style=\"lower-alpha\">\n<li data-mark-suffix=\".\">all people (maybe in a certain geographic area, such as the United States)<\/li>\n<li data-mark-suffix=\".\">a group of the people<\/li>\n<li data-mark-suffix=\".\">the proportion of all people who will buy the product<\/li>\n<li data-mark-suffix=\".\">the proportion of the sample who will buy the product<\/li>\n<li data-mark-suffix=\".\">[latex]X[\/latex] = the number of people who will buy it<\/li>\n<li data-mark-suffix=\".\">buy, not buy<\/li>\n<\/ol>\n<p>15. a<\/p>\n<p>17. b<\/p>\n<p>19. a<\/p>\n<p>21.<\/p>\n<ol id=\"fs-idm80641104\" data-number-style=\"lower-alpha\">\n<li>[latex]0.5242[\/latex]<\/li>\n<li>[latex]0.03[\/latex]%<\/li>\n<li>[latex]6.86[\/latex]%<\/li>\n<li>[latex]\\frac{823,088}{823,856}[\/latex]<\/li>\n<li>quantitative discrete<\/li>\n<li>quantitative continuous<\/li>\n<li>In both years, underwater earthquakes produced massive tsunamis.<\/li>\n<\/ol>\n<p>23. cluster<\/p>\n<p>25. convenience<\/p>\n<p>27.\u00a0values for [latex]X[\/latex], such as [latex]3[\/latex], [latex]4[\/latex], [latex]11[\/latex], and so on<\/p>\n<p>29.\u00a0No, we do not have enough information to make such a claim.<\/p>\n<p>31.\u00a0Take a simple random sample from each group. One way is by assigning a number to each patient and using a random number generator to randomly select patients.<\/p>\n<p>33.\u00a0This would be convenience sampling and is not random.<\/p>\n<p>35.\u00a0Yes, the sample size of [latex]150[\/latex] would be large enough to reflect a population of one school.<\/p>\n<p>37.\u00a0Even though the specific data support each researcher\u2019s conclusions, the different results suggest that more data need to be collected before the researchers can reach a conclusion.<\/p>\n<p>39.\u00a0There is not enough information given to judge if either one is correct or incorrect.<\/p>\n<p>41.\u00a0The software program seems to work because the second study shows that more patients improve while using the software than not. Even though the difference is not as large as that in the first study, the results from the second study are likely more reliable and still show improvement.<\/p>\n<p>43.\u00a0Yes, because we cannot tell if the improvement was due to the software or the exercise; the data is confounded, and a reliable conclusion cannot be drawn. New studies should be performed.<\/p>\n<p>45.\u00a0No, even though the sample is large enough, the fact that the sample consists of volunteers makes it a self-selected sample, which is not reliable.<\/p>\n<p>47.\u00a0No, even though the sample is a large portion of the population, two responses are not enough to justify any conclusions. Because the population is so small, it would be better to include everyone in the population to get the most accurate data.<\/p>\n<p>49.\u00a0quantitative discrete, [latex]150[\/latex]<\/p>\n<p>51.\u00a0qualitative, Oakland A\u2019s<\/p>\n<p>53.\u00a0quantitative discrete, [latex]11,234[\/latex] students<\/p>\n<p>55.\u00a0qualitative, Crest<\/p>\n<p>57.\u00a0quantitative continuous, [latex]47.3[\/latex] years<\/p>\n<p>59. b<\/p>\n<p>61.<\/p>\n<ol id=\"eip-idm59103408\" data-number-style=\"lower-alpha\">\n<li>The survey was conducted using six similar flights.\n<div data-type=\"newline\"><\/div>\n<p>The survey would not be a true representation of the entire population of air travelers.<\/p>\n<div data-type=\"newline\"><\/div>\n<p>Conducting the survey on a holiday weekend will not produce representative results.<\/li>\n<li>Conduct the survey during different times of the year.\n<div data-type=\"newline\"><\/div>\n<p>Conduct the survey using flights to and from various locations.<\/p>\n<div data-type=\"newline\"><\/div>\n<p>Conduct the survey on different days of the week.<\/li>\n<\/ol>\n<p>63.\u00a0Answers will vary. Sample Answer: You could use a systematic sampling method. Stop the tenth person as they leave one of the buildings on campus at 9:50 in the morning. Then stop the tenth person as they leave a different building on campus at 1:50 in the afternoon.<\/p>\n<p>65.\u00a0Answers will vary. Sample Answer: Many people will not respond to mail surveys. If they do respond to the surveys, you can\u2019t be sure who is responding. In addition, mailing lists can be incomplete.<\/p>\n<p>67. b<\/p>\n<p>69.\u00a0convenience cluster stratified systematic simple random<\/p>\n<p>71.<\/p>\n<ol id=\"eip-idp50853056\" data-mark-suffix=\".\" data-number-style=\"lower-alpha\">\n<li data-mark-suffix=\".\">qualitative<\/li>\n<li data-mark-suffix=\".\">quantitative discrete<\/li>\n<li data-mark-suffix=\".\">quantitative discrete<\/li>\n<li data-mark-suffix=\".\">qualitative<\/li>\n<\/ol>\n<p>73.\u00a0Causality: The fact that two variables are related does not guarantee that one variable is influencing the other. We cannot assume that crime rate impacts education level or that education level impacts crime rate.<\/p>\n<p>Confounding: There are many factors that define a community other than education level and crime rate. Communities with high crime rates and high education levels may have other lurking variables that distinguish them from communities with lower crime rates and lower education levels. Because we cannot isolate these variables of interest, we cannot draw valid conclusions about the connection between education and crime. Possible lurking variables include police expenditures, unemployment levels, region, average age, and size.<\/p>\n<p>75.<\/p>\n<ol id=\"fs-idm70068752\" data-number-style=\"lower-alpha\">\n<li>Possible reasons: increased use of caller id, decreased use of landlines, increased use of private numbers, voice mail, privacy managers, hectic nature of personal schedules, decreased willingness to be interviewed<\/li>\n<li>When a large number of people refuse to participate, then the sample may not have the same characteristics of the population. Perhaps the majority of people willing to participate are doing so because they feel strongly about the subject of the survey.<\/li>\n<\/ol>\n<p>77.<\/p>\n<ol id=\"eip-idm34826016\" data-element-type=\"enumerated\" data-number-style=\"lower-alpha\">\n<li>ordinal<\/li>\n<li>interval<\/li>\n<li>nominal<\/li>\n<li>nominal<\/li>\n<li>ratio<\/li>\n<li>ordinal<\/li>\n<li>nominal<\/li>\n<li>interval<\/li>\n<li>ratio<\/li>\n<li>interval<\/li>\n<li>ratio<\/li>\n<li>ordinal<\/li>\n<\/ol>\n<p>79.<\/p>\n<table id=\"eip-93\" summary=\"Filled Flossing Frequency for Adults with Gum Disease\">\n<thead>\n<tr>\n<th># Flossing per Week<\/th>\n<th>Frequency<\/th>\n<th>Relative Frequency<\/th>\n<th>Cumulative Relative Frequency<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>[latex]0[\/latex]<\/td>\n<td>[latex]27[\/latex]<\/td>\n<td>[latex]0.4500[\/latex]<\/td>\n<td>[latex]0.4500[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>[latex]1[\/latex]<\/td>\n<td>[latex]18[\/latex]<\/td>\n<td>[latex]0.3000[\/latex]<\/td>\n<td>[latex]0.7500[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>[latex]3[\/latex]<\/td>\n<td>[latex]11[\/latex]<\/td>\n<td>[latex]0.1833[\/latex]<\/td>\n<td>[latex]0.9333[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>[latex]6[\/latex]<\/td>\n<td>[latex]3[\/latex]<\/td>\n<td>[latex]0.0500[\/latex]<\/td>\n<td>[latex]0.9833[\/latex]<\/td>\n<\/tr>\n<tr>\n<td>[latex]7[\/latex]<\/td>\n<td>[latex]1[\/latex]<\/td>\n<td>[latex]0.0167[\/latex]<\/td>\n<td>[latex]1[\/latex]<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>b. [latex]5.00[\/latex]%<br \/>\nc. [latex]93.33[\/latex]%<\/p>\n<p>81.\u00a0The sum of the travel times is [latex]1,173.1[\/latex]. Divide the sum by [latex]50[\/latex] to calculate the mean value: [latex]23.462[\/latex]. Because each state\u2019s travel time was measured to the nearest tenth, round this calculation to the nearest hundredth: [latex]23.46[\/latex].<\/p>\n<p>83. b<\/p>\n<p>85.<\/p>\n<ol id=\"eip-idm79742704\" data-number-style=\"lower-alpha\">\n<li>Inmates may not feel comfortable refusing participation, or may feel obligated to take advantage of the promised benefits. They may not feel truly free to refuse participation.<\/li>\n<li>Parents can provide consent on behalf of their children, but children are not competent to provide consent for themselves.<\/li>\n<li>All risks and benefits must be clearly outlined. Study participants must be informed of relevant aspects of the study in order to give appropriate consent.<\/li>\n<\/ol>\n<p>87.<br \/>\nExplanatory variable: amount of sleep<\/p>\n<div data-type=\"newline\" data-count=\"1\"><\/div>\n<p>Response variable: performance measured in assigned tasks<\/p>\n<div data-type=\"newline\" data-count=\"1\"><\/div>\n<p>Treatments: normal sleep and [latex]27[\/latex] hours of total sleep deprivation<\/p>\n<div data-type=\"newline\" data-count=\"1\"><\/div>\n<p>Experimental Units: [latex]19[\/latex] professional drivers<\/p>\n<div data-type=\"newline\" data-count=\"1\"><\/div>\n<p>Lurking variables: none \u2013 all drivers participated in both treatments<\/p>\n<div data-type=\"newline\" data-count=\"1\"><\/div>\n<p>Random assignment: treatments were assigned in random order; this eliminated the effect of any \u201clearning\u201d that may take place during the first experimental session<\/p>\n<div data-type=\"newline\" data-count=\"1\"><\/div>\n<p>Control\/Placebo: completing the experimental session under normal sleep conditions<\/p>\n<div data-type=\"newline\" data-count=\"1\"><\/div>\n<p>Blinding: researchers evaluating subjects\u2019 performance must not know which treatment is being applied at the time<\/p>\n<p>89.\u00a0You cannot assume that the numbers of complaints reflect the quality of the airlines. The airlines shown with the greatest number of complaints are the ones with the most passengers. You must consider the appropriateness of methods for presenting data; in this case displaying totals is misleading<\/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-264\">\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>Introductory Statistics . <strong>Authored by<\/strong>: Barbara Illowski, Susan Dean. <strong>Provided by<\/strong>: Open Stax. <strong>Located at<\/strong>: <a target=\"_blank\" href=\"http:\/\/cnx.org\/contents\/30189442-6998-4686-ac05-ed152b91b9de@17.44\">http:\/\/cnx.org\/contents\/30189442-6998-4686-ac05-ed152b91b9de@17.44<\/a>. <strong>License<\/strong>: <em><a target=\"_blank\" rel=\"license\" href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY: Attribution<\/a><\/em>. <strong>License Terms<\/strong>: Download for free at http:\/\/cnx.org\/contents\/30189442-6998-4686-ac05-ed152b91b9de@17.44<\/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":21,"menu_order":9,"template":"","meta":{"_candela_citation":"[{\"type\":\"cc\",\"description\":\"Introductory Statistics \",\"author\":\"Barbara Illowski, Susan Dean\",\"organization\":\"Open Stax\",\"url\":\"http:\/\/cnx.org\/contents\/30189442-6998-4686-ac05-ed152b91b9de@17.44\",\"project\":\"\",\"license\":\"cc-by\",\"license_terms\":\"Download for free at http:\/\/cnx.org\/contents\/30189442-6998-4686-ac05-ed152b91b9de@17.44\"}]","CANDELA_OUTCOMES_GUID":"","pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-264","chapter","type-chapter","status-publish","hentry"],"part":237,"_links":{"self":[{"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/pressbooks\/v2\/chapters\/264","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/wp\/v2\/users\/21"}],"version-history":[{"count":5,"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/pressbooks\/v2\/chapters\/264\/revisions"}],"predecessor-version":[{"id":2252,"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/pressbooks\/v2\/chapters\/264\/revisions\/2252"}],"part":[{"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/pressbooks\/v2\/parts\/237"}],"metadata":[{"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/pressbooks\/v2\/chapters\/264\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/wp\/v2\/media?parent=264"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/pressbooks\/v2\/chapter-type?post=264"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/wp\/v2\/contributor?post=264"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/courses.lumenlearning.com\/frontrange-introstats1\/wp-json\/wp\/v2\/license?post=264"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}