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Gouges on a spindle. A tool-and-die machine shop produces extremely high-tolerance spindles. The spindles are 18-inch slender rods used in a variety of military equipment. A piece of equipment used in the manufacture of the spindles malfunctions on occasion and places a single gouge somewhere on the spindle. However, if the spindle can be cut so that it has 14 consecutive inches without a gouge, then the spindle can be salvaged for other purposes. Assuming that the location of the gouge along the spindle is random, what is the probability that a defective spindle can be salvaged?

Short Answer

Expert verified

The probability that a defective spindle can be salvaged is 0.4444.

Step by step solution

01

Given information

The spindle is an 18-inches slender rod. The defective spindle can be cut so that there are 14 consecutive inches without the gouge.

Let X represents the location of the gouge on the slender rod. Therefore, X is uniformly distributed between 0 inches and 18 inches.

02

Computing the probability of the defective spindle

The probability density function of X is:

fx=118;0x18.

One can 14 consecutive inches without the gouge if it is present within 4 inches of either side on the slender rod.

The probability that a defective spindle can be salvaged is obtained as:

PX<4+PX>14=P0<X<4+P14<X<18=4-018+18-1418=418+418=818=0.4444.

For the uniform distribution: P(a<X<b)=b-ad-c;ca<bd.

Thus, the required probability is 0.4444.

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Most popular questions from this chapter

Let t0 be a particular value of t. Use Table III in Appendix D to find t0 values such that the following statements are true.

a.=P(-t0<t<t0).95wheredf=10b.P(t-t0ortt0)wheredf=10c.P(tt0)=.05wheredf=10d.P(t-t0ortt0)=.10wheredf=20e.P(t-t0ortt0)=.01wheredf=5

Question: Performance ratings of government agencies. The U.S. Office of Management and Budget (OMB) requires government agencies to produce annual performance and accounting reports (PARS) each year. A research team at George Mason University evaluated the quality of the PARS for 24 government agencies (The Public Manager, Summer 2008), where evaluation scores ranged from 12 (lowest) to 60 (highest). The accompanying file contains evaluation scores for all 24 agencies for two consecutive years. (See Exercise 2.131, p. 132.) Data for a random sample of five of these agencies are shown in the accompanying table. Suppose you want to conduct a paired difference test to determine whether the true mean evaluation score of government agencies in year 2 exceeds the true mean evaluation score in year 1.

Source: J. Ellig and H. Wray, “Measuring Performance Reporting Quality,” The Public Manager, Vol. 37, No. 2, Summer 2008 (p. 66). Copyright © 2008 by Jerry Ellig. Used by permission of Jerry Ellig.

a. Explain why the data should be analyzedusing a paired difference test.

b. Compute the difference between the year 2 score and the year 1 score for each sampled agency.

c. Find the mean and standard deviation of the differences, part

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e. Give the rejection region for the test using a = .10.

f. Make the appropriate conclusion in the words of the problem.

Drug content assessment. Refer to Exercise 8.16 (p. 467)and the Analytical Chemistry (Dec. 15, 2009) study in which scientists used high-performance liquid chromatography to determine the amount of drug in a tablet. Recall that 25 tablets were produced at each of two different, independent sites. The researchers want to determine if the two sites produced drug concentrations with different variances. A Minitab printout of the analysis follows. Locate the test statistic and p-value on the printout. Use these values α=.05and to conduct the appropriate test for the researchers.

Test and CI for two Variances: Content vs Site

Method

Null hypothesis α1α2=1

Alternative hypothesis α1α21

F method was used. This method is accurate for normal data only.

Statistics

Site N St Dev Variance 95% CI for St Devs

1 25 3.067 9.406 (2.195,4.267)

2 25 3.339 11.147 (2.607,4.645)

Ratio of standard deviation =0.191

Ratio of variances=0.844

95% Confidence Intervals

Method CI for St Dev Ratio CI Variance Ratio

F (0.610, 1.384) (0.372, 1.915)

Tests

Method DF1 DF2 Test statistic p-value

F 24 24 0.84 0.681

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a.P(zz0)=0.2090b.P(zz0)=0.7090c.P(-z0z<z0)=0.8472d.P(-z0z<z0)=0.1664e.P(z0zz0)=0.4798f.P(-1<z<z0)

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