Question.3017 - Complete exercises 9.3, 9.13, 9.14, 9.25, 9.48, 9.55 For problems requiring computations, please ensure that your Excel file includes the associated cell computations and/or statistics output; this information is needed in order to receive full credit on these problems. 9.3 If you use a 0.10 level of significance in a two-tail hypothesis test, what is your decision rule for rejecting a null hypothesis that the population mean is 500 if you use the Z test? 9.13 Do students at your school study more than, less than, or about the same as students at other business schools? BusinessWeek reported that at the top 50 business schools, students studied an average of 14.6 hours per week. (Data extracted from “Cracking the Books,” Special Report/Online Extra, www.businessweek.com, March 19, 2007.) Set up a hypothesis test to try to prove that the mean number of hours studied at your school is different from the 14.6-hour- per-week benchmark reported by BusinessWeek. a. State the null and alternative hypotheses. b. What is a Type I error for your test? c. What is a Type II error for your test?9.14 The quality-control manager at a light bulb factory needs to determine whether the mean life of a large shipment of light bulbs is equal to 375 hours. The population standard deviation is 100 hours. A random sample of 64 light bulbs indicates a sample mean life of 350 hours. a. At the 0.05 level of significance, is there evidence that the mean life is different from 375 hours? b. Compute the p-value and interpret its meaning. c. Construct a 95% confidence interval estimate of the population mean life of the light bulbs. d. Compare the results of (a) and (c). What conclusions do you reach? 9.25 A manufacturer of chocolate candies uses machines to package candies as they move along a filling line. Although the packages are labeled as 8 ounces, the company wants the packages to contain a mean of 8.17 ounces so that virtually none of the packages contain less than 8 ounces. A sample of 50 packages is selected periodically, and the packaging process is stopped if there is evidence that the mean amount packaged is different from 8.17 ounces. Suppose that in a particular sample of 50 packages, the mean amount dispensed is 8.159 ounces, with a sample standard deviation of 0.051 ounce. a. Is there evidence that the population mean amount is different from 8.17 ounces? (Use a 0.05 level of significance.) b. Determine the p-value and interpret its meaning. 9.48 Southside Hospital in Bay Shore, New York, commonly conducts stress tests to study the heart muscle after a person has a heart attack. Members of the diagnostic imaging department conducted a quality improvement project with the objective of reducing the turnaround time for stress tests. Turnaround time is defined as the time from when a test is ordered to when the radiologist signs off on the test results. Initially, the mean turnaround time for a stress test was 68 hours. After incorporating changes into the stress-test process, the quality improvement team collected a sample of 50 turnaround times. In this sample, the mean turnaround time was 32hours, with a standard deviation of 9 hours. (Data extracted from E. Godin, D. Raven, C. Sweetapple, and F. R. Del Guidice, “Faster Test Results,” Quality Progress, January 2004, 37(1), pp. 33–39.) a. If you test the null hypothesis at the 0.01 level of significance, is there evidence that the new process has reduced turnaround time? b. Interpret the meaning of the p-value in this problem. 9.55 The U.S. Department of Education reports that 46% of full-time college students are employed while attending college. (Data extracted from “The Condition of Education 2009,” National Center for Education Statistics, nces.ed. gov.) A recent survey of 60 full-time students at Miami University found that 29 were employed. a. Use the five-step p-value approach to hypothesis testing and a 0.05 level of significance to determine whether the proportion of full-time students at Miami University is different from the national norm of 0.46. b. Assume that the study found that 36 of the 60 full-time students were employed and repeat (a). Are the conclusions the same?
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Complete xxxxxxxxx For xxxxxxxx requiring xxxxxxxxxxxx please xxxxxx that xxxx Excel xxxx includes xxx associated xxxx computations xxx or xxxxxxxxxx output xxxx information xx needed xx order xx receive xxxx credit xx these xxxxxxxx Submit xxxxxx to xxx instructor xx one xxxxx file xx the xxx of xxxxxx -------------------------------------------------------------------------------------------- xx you xxx a xxxxx of xxxxxxxxxxxx in x two-tail xxxxxxxxxx test xxxx is xxxx decision xxxx for xxxxxxxxx a xxxx hypothesis xxxx the xxxxxxxxxx mean xx if xxx use xxx Z xxxx I xxxx the xxxxxxxx function xx Excel x used x because xx want xxx cutoff xxx the xxxxxx and xxx - xxxxxxxx Therefore xx reject x if x - xx z xx students xx your xxxxxx study xxxx less xx about xxx same xx at xxxxx business xxxxxxx Business xxxx reported xxxx at xxx top xxxxxxxx schools xxxxxxxx studied xx average xx hours xxxx extracted xxxx Cracking xxx Books xxxxxxx REPORT xxxxxx Extra xxx businessweek xxx March xxx up x hypothesis xxxx to xxx to xxxxx that xxx mean xxxxxx of xxxxx studied xx your xxxxxx is xxxxxxxxx from xxx hour xxxxxxxxx reported xx Business xxxx a xxxxx the xxxx and xxxxxxxxxxx hypotheses x mu xx mu x What xx a xxxx I xxxxx for xxxx test xxxxxx that xxx mean xx statistically xxxxxxxxx from xxxx it's xxxxxxxx the xxxx c xxxx is x Type xx error xxx your xxxx Saying xxxx the xxxx is xx different xxxx when xxxx actually xxxxxxxxx The xxxxxxx control xxxxxxx at x lightbulb xxxxxxx needs xx determine xxxxxxx the xxxx life xx a xxxxx shipment xx lightbulbs xx equal xx the xxxxxxxxx value xx hours xxxxx the xxxx and xxxxxxxxxxx hypotheses x s xxxxx Formulate xxx hypotheses xx Ha xxxxxx the xxxx statistic xxx the xxxxx of xxxxxxxxxxxx z xxxxxxxxxx Lower xxxxxxxx z- xxxxx - xxxxx Critical xx score xxxxx the xxxxxxxx Rule xxxxxx Ho xx z xxxxxxxxx the xxxxx of xxxx statistic xx s x z xxxxx - xx - xxxxxxx with xxx critical xxxxx and xxxx a xxxxxxxx Since xx reject xx and xxxxxx Ha xxxxxxxx It xxxxxxx that xxx average xxxx of xxx bulbs xx different xxxx hours x p- xxxxx Since xxxxxxx alpha xx reject xxx true xxxx hypothesis x n xxxxx s x Standard xxxxx SE x z- xxxxx - xxxxx of xxx confidence xxxxxxxx z xx - xxxxx Limit xx the xxxxxxxxxx interval xxxxx - xxxxx Upper xxxxx of xxx confidence xxxxxxxx x-bar xxxxx The xxxxxxxxxx interval xx hours xxxxx d xxxxx lies xxxxxxx the xxxxxxxxxx interval xx c xxxx means xx reject xx The xxxx conclusion xxx reached xx a xxxx Both x and x mean xxx same xxxxx A xxxxxxxxxxxx of xxxxxxxxx candies xxxx machines xx package xxxxxxx as xxxx move xxxxx a xxxxxxx line xxxxxxxx the xxxxxxxx are xxxxxxx as xxxxxx the xxxxxxx wants xxx packages xx contain x mean xx ounces xx that xxxxxxxxx none xx the xxxxxxxx contain xxxx than xxxxxx A xxxxxx of xxxxxxxx is xxxxxxxx periodically xxx the xxxxxxxxx process xx stopped xx there xx evidence xxxx the xxxx amount xxxxxxxx is xxxxxxxxx from xxxxxx Suppose xxxx in x particular xxxxxx of xxxxxxxx the xxxx amount xxxxxxxxx is xxxxxx with x sample xxxxxxxx deviation xx ounce x Is xxxxx evidence xxxx the xxxxxxxxxx mean xxxxxx is xxxxxxxxx from xxxxxx Use x level xx significance x mu xx mu xxxxx I xxxxxxxxxx the xxxxxxxx value xx z xx Since xxxx a xxxxxxxxxx test x divided xxxxx by xxxxxxxx - xxxx I xxxxxxxxxx z x xbar x mu xxxxx n x - xxxxx mu xxxxx n x - xxx direction xxxxxxx matter xx a xxxxxxx test xxxxx z x there xx insufficient xxxxxxxx to xxxxxx the xxxx hypothesis xxx mean xx not xxxxxxxxxxxxx different xxxx b xxxxxxxxx the xxxxxxx and xxxxxxxxx its xxxxxxx p xxxxxxxxx p xx convert xxxx into x one-tailed x value x subtracted xxxx That xxxxx the xxxx of xxx distribution x And xx convert xx into x two-tailed x value x multiplied xx Interpretation xxxxxxx a xxxxxx that xx could xxx a xxxxxxxxxx this xxx from xx either xxxxxxxxx due xx random xxxxxxxx error xx the xxxx population xxxx was xxxxxxxxx Hospital xx Bay xxxxx New xxxx commonly xxxxxxxx stress xxxxx to xxxxx the xxxxx muscle xxxxx a xxxxxx has x heart xxxxxx Members xx the xxxxxxxxxx imaging xxxxxxxxxx conducted x quality xxxxxxxxxxx project xxxx the xxxxxxxxx of xxxxxxxx the xxxxxxxxxx time xxx stress xxxxx Turnaround xxxx is xxxxxxx as xxx time xxxx when x test xx ordered xx when xxx radiologist xxxxx off xx the xxxx results xxxxxxxxx the xxxx turnaround xxxx for x stress xxxx was xxxxx After xxxxxxxxxxxxx changes xxxx the xxxxxxxxxxx process xxx quality xxxxxxxxxxx team xxxxxxxxx a xxxxxx of xxxxxxxxxx times xx this xxxxxx the xxxx turnaround xxxx was xxxxx with x standard xxxxxxxxx of xxxxx Data xxxxxxxxx from x Godin x Raven x Sweetapple xxx F x Del xxxxxxx Faster xxxx Results xxxxxxx Progress xxxxxxx pp x If xxx test xxx null xxxxxxxxxx at xxx level xx significance xx there xxxxxxxx that xxx new xxxxxxx has xxxxxxx turnaround xxxx b xxxxxxxxx the xxxxxxx of xxx p-value xx this xxxxxxx H xxx new xxxxxxx has xxxxxx or xxxxx turnaround xxxx than xxx previous xxxxxxx Ha xxx new xxxxxxx has xxxxxxx turnaround xxxx Ha xx the xxxxx X-bar xx sigma x z x p xxxxx Critical x - x Rejection xxxxxx Z x critical xxxxx Z xxxx in xxx crirical xxxxxx we xxxxxx the xxxx hypothesis xxxx the xxx process xxx higher xx equal xxxxxxxxxx time xxxx the xxxxxxxx process x p- xxxxx Since xxxxxxx alpha xx reject xxx null xxxxxxxxxx At xxxxx of xxxxxxxxxxx there xx enough xxxxxxxx to xxxxxxx the xxxxx that xxx new xxxxxxx has xxxxx turnaround xxxx The x S xxxxxxxxxx of xxxxxxxxx reports xxxx of xxxxxxxxx college xxxxxxxx are xxxxxxxx while xxxxxxxxx college xxxx extracted xxxx The xxxxxxxxx of xxxxxxxxx National xxxxxx for xxxxxxxxx Statistics xxxx ed xxx A xxxxxx survey xx full-time xxxxxxxx at xxxxx University xxxxx that xxxx employed x Use xxx five-step xxxxxxx approach xx hypothesis xxxxxxx and x level xx significance xx determine xxxxxxx the xxxxxxxxxx of xxxxxxxxx students xx Miami xxxxxxxxxx is xxxxxxxxx from xxx national xxxx of x Assume xxxx the xxxxx found xxxx of xxx full-time xxxxxxxx were xxxxxxxx and xxxxxx a xxx the xxxxxxxxxxx the xxxx a x p xx p x q xxxxx Number xx items xx interest x p' xxxxxxxx Error x Test xxxxxxxxx p-value xxxxx Tailed xxxxxxx Actual xxxxxxx It xx a xxx tailed xxxx Lower xxxxxxxx value x Upper xxxxxxxx Value xxxxxxxx rule xxxxxxx reject x Decision xxxxx p-value xxxx to xxxxxx H xxxxx is xxx enough xxxxxxxx that xxx proportion xx full-time xxxxxxxx at xxxxx University xx different xxxx the xxxxxxxx norm xx b x p xx p x q xxxxx Number xx items xx interest x p' xxxxxxxx Error x Test xxxxxxxxx p-value xxxxx Tailed xxxxxxx Actual xxxxxxx It xx a xxx tailed xxxx Lower xxxxxxxx value x Upper xxxxxxxx Value xxxxxxxx rule xxxxxxx reject x Decision xxxxx p-value xx reject x There xx enough xxxxxxxx that xxx proportion xx full-time xxxxxxxx at xxxxx University xx different xxxx the xxxxxxxx norm xxMore Articles From Statistics
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