{"id":2818,"date":"2022-05-07T20:43:19","date_gmt":"2022-05-08T00:43:19","guid":{"rendered":"https:\/\/openbooks.macewan.ca\/rcommander\/?post_type=chapter&#038;p=2818"},"modified":"2024-01-23T23:29:55","modified_gmt":"2024-01-24T04:29:55","slug":"8-8-review-questions","status":"publish","type":"chapter","link":"https:\/\/openbooks.macewan.ca\/introstats\/chapter\/8-8-review-questions\/","title":{"raw":"8.8 Review Questions","rendered":"8.8 Review Questions"},"content":{"raw":"<ol>\r\n \t<li>Determine whether the following interpretations of a 95% confidence interval (337, 343) ml for the population mean volume of beer [latex]\\mu[\/latex] are true or false. If false, correct it.\r\n<ol type=\"a\">\r\n \t<li>We can be 95% confident that [latex]\\mu[\/latex] is somewhere between 337 ml and 343 ml.<\/li>\r\n \t<li>We can be 95% confident that the sample mean [latex]\\bar x[\/latex] is somewhere between 337 and 343 ml.<\/li>\r\n \t<li>The probability that the population mean [latex]\\mu[\/latex] is within the interval (337, 343) is 0.95.<\/li>\r\n \t<li>The probability that the sample mean [latex]\\bar x[\/latex] is within the interval (337, 343) is 0.95.<\/li>\r\n \t<li>95% of the [latex]\\bar x[\/latex] values are within the interval (337, 343).<\/li>\r\n<\/ol>\r\n<\/li>\r\n \t<li>Determine whether the following statements about the [latex]P[\/latex]-value are true or false. If false, correct it.\r\n<ol type=\"a\">\r\n \t<li>We should reject the null hypothesis [latex]H_0[\/latex] if the [latex]P[\/latex]-value[latex]\\le \\alpha[\/latex].<\/li>\r\n \t<li>We should accept the null [latex]H_0[\/latex] if the [latex]P[\/latex]-value[latex]&gt; \\alpha[\/latex].<\/li>\r\n \t<li>[latex]P[\/latex]-value is the probability that the null [latex]H_0[\/latex] is true.<\/li>\r\n \t<li>[latex]P[\/latex]-value is the probability of rejecting [latex]H_0[\/latex].<\/li>\r\n<\/ol>\r\n<\/li>\r\n \t<li>Suppose you perform a statistical test to decide whether a nuclear reactor should be approved. Further, suppose that failing to reject the null hypothesis (the reactor is safe to use) corresponds to approval.\r\n<ol type=\"a\">\r\n \t<li>Write down the null and alternative hypotheses.<\/li>\r\n \t<li>What are the type I and type II errors in this example?<\/li>\r\n \t<li>Which error has more serious consequence, type I or type II? Would you like to set [latex]\\alpha[\/latex] or [latex]\\beta[\/latex] to be relatively small?<\/li>\r\n<\/ol>\r\n<\/li>\r\n \t<li>The mean retail price of agriculture books in 2005 was $57.61. This year\u2019s retail mean price for 28 randomly selected agriculture books was $54.97. Assume that the population standard deviation of prices for this year\u2019s agriculture books is $8.45.\r\n<ol type=\"a\">\r\n \t<li>At the 10% significance level, do the data provide sufficient evidence to conclude that this year\u2019s mean retail price of agriculture books has changed from the 2005 mean?<\/li>\r\n \t<li>What is the [latex]P[\/latex]-value of the test in part (a)?<\/li>\r\n \t<li>Obtain a confidence interval corresponding to the test in part (a).<\/li>\r\n \t<li>Does the interval obtained in part (c) support the result in part (a)?<\/li>\r\n<\/ol>\r\n<\/li>\r\n \t<li>The ankle brachial index (ABI) compares the blood pressure of a patient\u2019s arm to the blood pressure of the patient\u2019s leg. The ABI can be an indicator of different diseases, including arterial diseases. A healthy (or normal) ABI is 0.9 or greater. Researchers obtained the ABI of 100 women with peripheral arterial disease and obtained a mean ABI of 0.64 with a standard deviation of 0.15.\r\n<ol type=\"a\">\r\n \t<li>At the 5% significance level, do the data provide sufficient evidence that, on average, women with peripheral arterial disease have an unhealthy ABI?<\/li>\r\n \t<li>What is the [latex]P[\/latex]-value of the test in part (a)?<\/li>\r\n \t<li>Obtain a confidence interval corresponding to the test in part (a).<\/li>\r\n \t<li>Does the interval obtained in part (c) support the conclusion in part (a)?<\/li>\r\n<\/ol>\r\n<\/li>\r\n<\/ol>\r\n<details><summary>Show\/Hide Answer<\/summary>\r\n<ol>\r\n \t<li>\u200c\r\n<ol type=\"a\">\r\n \t<li>True, a standard way to interpret the confidence interval.<\/li>\r\n \t<li>False. The sample mean [latex]\\bar{x}[\/latex] is the center of the interval; we should be 100% confident that the sample mean [latex]\\bar{x}[\/latex] is in the interval.<\/li>\r\n \t<li>False. There is no randomness here and hence there is no probability, since the population mean [latex]\\mu[\/latex] is a constant and the interval (337, 343) is also fixed. [latex]\\mu[\/latex] is either within the interval or outside the interval.<\/li>\r\n \t<li>False. Similar arguments as the previous. The sample mean [latex]\\bar{\\mu}[\/latex] is a fixed number, and the interval is also fixed; there is no randomness.<\/li>\r\n \t<li>False. 95% of the [latex]\\bar{\\mu}[\/latex] values are within the interval [latex]( \\mu - 1.96 \\frac{\\sigma}{\\sqrt{n}}, \\mu + 1.96 \\frac{\\sigma}{\\sqrt{n}} ).[\/latex]<\/li>\r\n<\/ol>\r\n<\/li>\r\n \t<li>\u200c\r\n<ol type=\"a\">\r\n \t<li>True.<\/li>\r\n \t<li>False. In general, never accept [latex]H_0[\/latex].<\/li>\r\n \t<li>False. P-value measures the strength of the evidence that the data contradicts [latex]H_0[\/latex] and is in favour of [latex]H_a[\/latex].<\/li>\r\n \t<li>False. P-value is the probability of observing [latex]z_0 (t_0)[\/latex] or more extreme values.<\/li>\r\n<\/ol>\r\n<\/li>\r\n \t<li>\u200c\r\n<ol type=\"a\">\r\n \t<li>[latex]H_0 [\/latex]: the nuclear reactor is safe versus [latex]H_a[\/latex]: the nuclear reactor is not safe.<\/li>\r\n \t<li>Type I error: disapprove of the nuclear reactor of ruse given that the nuclear reactor is actually safe.\r\nType II error: approve the nuclear reactor for use given that the nuclear reactor is not safe.<\/li>\r\n \t<li>Type II error is more severe than type I. We probably need to set the type II error rate relatively small.<\/li>\r\n<\/ol>\r\n<\/li>\r\n \t<li>\u200c\r\n<ol type=\"a\">\r\n \t<li>Assumptions:\r\nWe have a simple random sample.\r\nWe have a large sample with [latex]n=100 &gt;30.[\/latex]\r\nPopulation standard deviation [latex]\\sigma[\/latex] is unknown.\r\nWe can use a one-sample t-test. Summarize the information: [latex]n =100, \\bar{x} = 0.64, s= 0.15[\/latex]. The six steps to perform a one-sample t-test are:\r\n<ol>\r\n \t<li>Hypotheses: [latex]H_0: \\mu \\ge 0.9 \\text{ versus } H_a : \\mu &lt; 0.9.[\/latex]<\/li>\r\n \t<li>The significance level [latex]\\alpha = 0.05.[\/latex]<\/li>\r\n \t<li>Observed test statistic:\r\n[latex] t_o = \\frac{\\bar{x} - \\mu_0}{s \/ \\sqrt{n}} = \\frac{0.64 - 0.9}{ 0.15 \/ \\sqrt{100}} = -17,333[\/latex]\r\nwith [latex]df = n -1 = 99.[\/latex]<\/li>\r\n \t<li>A left-tailed test, P-value = [latex]P( t \\le t_0 ) = P(t \\le -17.333 ) = P(t \\ge 17.333 ) &lt; 0.005[\/latex].<\/li>\r\n \t<li>Since P-value &lt; 0.005 &lt; 0.05[latex](\\alpha)[\/latex], we reject [latex]H_0[\/latex].<\/li>\r\n \t<li>At the 5% significance level, we have sufficient evidence that, on average, women with peripheral arterial disease have an unhealthy ABI<\/li>\r\n<\/ol>\r\n<\/li>\r\n \t<li>P-value &lt; 0.005<\/li>\r\n \t<li>A left-tailed test at significance level [latex]\\alpha = 0.05[\/latex] corresponds to a [latex]( 1- \\alpha ) \\times 100%[\/latex] lower-tailed confidence interval. With df = 99 not given in Table IV, use df = 90 the closed one but still no more than 99, [latex]\\alpha =0.05 \\Longrightarrow t_{\\alpha} = t_{0.05} = 1.662[\/latex]\r\n[latex] (-\\infty, \\bar{x} + t_{\\alpha} \\frac{s}{\\sqrt{n}} ) \u00a0= ( -\\infty, 0.64 + 1.662 \\times \\frac{0.15}{\\sqrt{100}} ) = (-\\infty, 0.665). [\/latex]\r\nInterpretation: we can be 95% confident that the mean ABI of women with peripheral arterial disease is somewhere below 0.665.\r\nNote: In this course, you are only required to know how to obtain a two-tailed interval. For df=99 (use 90), [latex]t_{\\alpha \/ 2} = t_{0.025} = 1.987[\/latex]. The 95% two-tailed interval is\r\n[latex] \\bar{x} \\pm t_{\\alpha\/2}\\frac{s}{\\sqrt{n}} = 0.64 \\pm 1.987 \\times \\frac{0.15}{\\sqrt{100}} = (0.610, 0.670). [\/latex]\r\nInterpretation: we can be 95% confident that the mean ABI of women with peripheral arterial disease is somewhere between 0.610 and 0.670. The entire interval is below 0.9, so we can claim [latex]\\mu &lt; 0.9.[\/latex]<\/li>\r\n \t<li>Yes, since a healthy (or normal) ABI is 0.9 or greater; however, 0.9 is outside the confidence interval (it is above the entire interval), so we can claim that the mean ABI of women with peripheral arterial disease is below 0.9, i.e., [latex]\\mu &lt; 0.9[\/latex]. This is consistent with the conclusion of the t-test in part a).<\/li>\r\n<\/ol>\r\n<\/li>\r\n<\/ol>\r\n<\/details>","rendered":"<ol>\n<li>Determine whether the following interpretations of a 95% confidence interval (337, 343) ml for the population mean volume of beer [latex]\\mu[\/latex] are true or false. If false, correct it.\n<ol type=\"a\">\n<li>We can be 95% confident that [latex]\\mu[\/latex] is somewhere between 337 ml and 343 ml.<\/li>\n<li>We can be 95% confident that the sample mean [latex]\\bar x[\/latex] is somewhere between 337 and 343 ml.<\/li>\n<li>The probability that the population mean [latex]\\mu[\/latex] is within the interval (337, 343) is 0.95.<\/li>\n<li>The probability that the sample mean [latex]\\bar x[\/latex] is within the interval (337, 343) is 0.95.<\/li>\n<li>95% of the [latex]\\bar x[\/latex] values are within the interval (337, 343).<\/li>\n<\/ol>\n<\/li>\n<li>Determine whether the following statements about the [latex]P[\/latex]-value are true or false. If false, correct it.\n<ol type=\"a\">\n<li>We should reject the null hypothesis [latex]H_0[\/latex] if the [latex]P[\/latex]-value[latex]\\le \\alpha[\/latex].<\/li>\n<li>We should accept the null [latex]H_0[\/latex] if the [latex]P[\/latex]-value[latex]> \\alpha[\/latex].<\/li>\n<li>[latex]P[\/latex]-value is the probability that the null [latex]H_0[\/latex] is true.<\/li>\n<li>[latex]P[\/latex]-value is the probability of rejecting [latex]H_0[\/latex].<\/li>\n<\/ol>\n<\/li>\n<li>Suppose you perform a statistical test to decide whether a nuclear reactor should be approved. Further, suppose that failing to reject the null hypothesis (the reactor is safe to use) corresponds to approval.\n<ol type=\"a\">\n<li>Write down the null and alternative hypotheses.<\/li>\n<li>What are the type I and type II errors in this example?<\/li>\n<li>Which error has more serious consequence, type I or type II? Would you like to set [latex]\\alpha[\/latex] or [latex]\\beta[\/latex] to be relatively small?<\/li>\n<\/ol>\n<\/li>\n<li>The mean retail price of agriculture books in 2005 was $57.61. This year\u2019s retail mean price for 28 randomly selected agriculture books was $54.97. Assume that the population standard deviation of prices for this year\u2019s agriculture books is $8.45.\n<ol type=\"a\">\n<li>At the 10% significance level, do the data provide sufficient evidence to conclude that this year\u2019s mean retail price of agriculture books has changed from the 2005 mean?<\/li>\n<li>What is the [latex]P[\/latex]-value of the test in part (a)?<\/li>\n<li>Obtain a confidence interval corresponding to the test in part (a).<\/li>\n<li>Does the interval obtained in part (c) support the result in part (a)?<\/li>\n<\/ol>\n<\/li>\n<li>The ankle brachial index (ABI) compares the blood pressure of a patient\u2019s arm to the blood pressure of the patient\u2019s leg. The ABI can be an indicator of different diseases, including arterial diseases. A healthy (or normal) ABI is 0.9 or greater. Researchers obtained the ABI of 100 women with peripheral arterial disease and obtained a mean ABI of 0.64 with a standard deviation of 0.15.\n<ol type=\"a\">\n<li>At the 5% significance level, do the data provide sufficient evidence that, on average, women with peripheral arterial disease have an unhealthy ABI?<\/li>\n<li>What is the [latex]P[\/latex]-value of the test in part (a)?<\/li>\n<li>Obtain a confidence interval corresponding to the test in part (a).<\/li>\n<li>Does the interval obtained in part (c) support the conclusion in part (a)?<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<details>\n<summary>Show\/Hide Answer<\/summary>\n<ol>\n<li>\u200c\n<ol type=\"a\">\n<li>True, a standard way to interpret the confidence interval.<\/li>\n<li>False. The sample mean [latex]\\bar{x}[\/latex] is the center of the interval; we should be 100% confident that the sample mean [latex]\\bar{x}[\/latex] is in the interval.<\/li>\n<li>False. There is no randomness here and hence there is no probability, since the population mean [latex]\\mu[\/latex] is a constant and the interval (337, 343) is also fixed. [latex]\\mu[\/latex] is either within the interval or outside the interval.<\/li>\n<li>False. Similar arguments as the previous. The sample mean [latex]\\bar{\\mu}[\/latex] is a fixed number, and the interval is also fixed; there is no randomness.<\/li>\n<li>False. 95% of the [latex]\\bar{\\mu}[\/latex] values are within the interval [latex]( \\mu - 1.96 \\frac{\\sigma}{\\sqrt{n}}, \\mu + 1.96 \\frac{\\sigma}{\\sqrt{n}} ).[\/latex]<\/li>\n<\/ol>\n<\/li>\n<li>\u200c\n<ol type=\"a\">\n<li>True.<\/li>\n<li>False. In general, never accept [latex]H_0[\/latex].<\/li>\n<li>False. P-value measures the strength of the evidence that the data contradicts [latex]H_0[\/latex] and is in favour of [latex]H_a[\/latex].<\/li>\n<li>False. P-value is the probability of observing [latex]z_0 (t_0)[\/latex] or more extreme values.<\/li>\n<\/ol>\n<\/li>\n<li>\u200c\n<ol type=\"a\">\n<li>[latex]H_0[\/latex]: the nuclear reactor is safe versus [latex]H_a[\/latex]: the nuclear reactor is not safe.<\/li>\n<li>Type I error: disapprove of the nuclear reactor of ruse given that the nuclear reactor is actually safe.<br \/>\nType II error: approve the nuclear reactor for use given that the nuclear reactor is not safe.<\/li>\n<li>Type II error is more severe than type I. We probably need to set the type II error rate relatively small.<\/li>\n<\/ol>\n<\/li>\n<li>\u200c\n<ol type=\"a\">\n<li>Assumptions:<br \/>\nWe have a simple random sample.<br \/>\nWe have a large sample with [latex]n=100 >30.[\/latex]<br \/>\nPopulation standard deviation [latex]\\sigma[\/latex] is unknown.<br \/>\nWe can use a one-sample t-test. Summarize the information: [latex]n =100, \\bar{x} = 0.64, s= 0.15[\/latex]. The six steps to perform a one-sample t-test are:<\/p>\n<ol>\n<li>Hypotheses: [latex]H_0: \\mu \\ge 0.9 \\text{ versus } H_a : \\mu < 0.9.[\/latex]<\/li>\n<li>The significance level [latex]\\alpha = 0.05.[\/latex]<\/li>\n<li>Observed test statistic:<br \/>\n[latex]t_o = \\frac{\\bar{x} - \\mu_0}{s \/ \\sqrt{n}} = \\frac{0.64 - 0.9}{ 0.15 \/ \\sqrt{100}} = -17,333[\/latex]<br \/>\nwith [latex]df = n -1 = 99.[\/latex]<\/li>\n<li>A left-tailed test, P-value = [latex]P( t \\le t_0 ) = P(t \\le -17.333 ) = P(t \\ge 17.333 ) < 0.005[\/latex].<\/li>\n<li>Since P-value &lt; 0.005 &lt; 0.05[latex](\\alpha)[\/latex], we reject [latex]H_0[\/latex].<\/li>\n<li>At the 5% significance level, we have sufficient evidence that, on average, women with peripheral arterial disease have an unhealthy ABI<\/li>\n<\/ol>\n<\/li>\n<li>P-value &lt; 0.005<\/li>\n<li>A left-tailed test at significance level [latex]\\alpha = 0.05[\/latex] corresponds to a [latex]( 1- \\alpha ) \\times 100%[\/latex] lower-tailed confidence interval. With df = 99 not given in Table IV, use df = 90 the closed one but still no more than 99, [latex]\\alpha =0.05 \\Longrightarrow t_{\\alpha} = t_{0.05} = 1.662[\/latex]<br \/>\n[latex](-\\infty, \\bar{x} + t_{\\alpha} \\frac{s}{\\sqrt{n}} ) \u00a0= ( -\\infty, 0.64 + 1.662 \\times \\frac{0.15}{\\sqrt{100}} ) = (-\\infty, 0.665).[\/latex]<br \/>\nInterpretation: we can be 95% confident that the mean ABI of women with peripheral arterial disease is somewhere below 0.665.<br \/>\nNote: In this course, you are only required to know how to obtain a two-tailed interval. For df=99 (use 90), [latex]t_{\\alpha \/ 2} = t_{0.025} = 1.987[\/latex]. The 95% two-tailed interval is<br \/>\n[latex]\\bar{x} \\pm t_{\\alpha\/2}\\frac{s}{\\sqrt{n}} = 0.64 \\pm 1.987 \\times \\frac{0.15}{\\sqrt{100}} = (0.610, 0.670).[\/latex]<br \/>\nInterpretation: we can be 95% confident that the mean ABI of women with peripheral arterial disease is somewhere between 0.610 and 0.670. The entire interval is below 0.9, so we can claim [latex]\\mu < 0.9.[\/latex]<\/li>\n<li>Yes, since a healthy (or normal) ABI is 0.9 or greater; however, 0.9 is outside the confidence interval (it is above the entire interval), so we can claim that the mean ABI of women with peripheral arterial disease is below 0.9, i.e., [latex]\\mu < 0.9[\/latex]. This is consistent with the conclusion of the t-test in part a).<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/details>\n","protected":false},"author":19,"menu_order":8,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":[],"pb_section_license":""},"chapter-type":[],"contributor":[],"license":[],"class_list":["post-2818","chapter","type-chapter","status-publish","hentry"],"part":889,"_links":{"self":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapters\/2818","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/wp\/v2\/users\/19"}],"version-history":[{"count":19,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapters\/2818\/revisions"}],"predecessor-version":[{"id":5044,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapters\/2818\/revisions\/5044"}],"part":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/parts\/889"}],"metadata":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapters\/2818\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/wp\/v2\/media?parent=2818"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/pressbooks\/v2\/chapter-type?post=2818"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/wp\/v2\/contributor?post=2818"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/openbooks.macewan.ca\/introstats\/wp-json\/wp\/v2\/license?post=2818"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}