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Public Function BuildString() Dim retString As String If Cache( BuildString ) Is Nothing Then Dim x As Integer = 0 Dim s As New System.Text.StringBuilder() Dim pcStringLength As PerformanceCounter Dim pcLoopValue As PerformanceCounter pcStringLength = CType(Session( pcStringLength ), _ PerformanceCounter) pcLoopValue = CType(Session( pcLoopVaue ), _ PerformanceCounter) Trace.Warn( BuildString , Start of loop ) For x = 1 To 3000 s.Append( abcdefghijklmnopqrstuvwxyz The value of x= ) s.Append(x.ToString()) s.Append( <br> ) Update the counters. pcStringLength.RawValue = s.Length pcLoopValue.RawValue = x Next Trace.Warn( BuildString , End of loop ) Clear the counters. pcStringLength.RawValue = 0 pcLoopValue.RawValue = 0

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x2 426 F, and s2 3 F Do the sample data support the claim that both alloys have the same melting point Use 005 and assume that both populations are normally distributed and have the same standard deviation Find the P-value for the test 10-26 Referring to the melting point experiment in Exercise 10-25, suppose that the true mean difference in melting points is 3 F How large a sample would be required to detect this difference using an 005 level test with probability at least 09 Use 1 4 as an initial esti2 mate of the common standard deviation 10-27 Two companies manufacture a rubber material intended for use in an automotive application The part will be subjected to abrasive wear in the eld application, so we decide to compare the material produced by each company in a test.

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Twenty- ve samples of material from each company are tested in an abrasion test, and the amount of wear after 1000 cycles is observed For company 1, the sample mean and standard deviation of wear are x1 20 milligrams /1000 cycles and s1 2 milligrams/1000 cycles, while for company 2 we obtain x2 15 milligrams/1000 cycles and s2 8 milligrams/1000 cycles (a) Do the data support the claim that the two companies produce material with different mean wear Use 005, and assume each population is normally distributed but that their variances are not equal (b) What is the P-value for this test (c) Do the data support a claim that the material from company 1 has higher mean wear than the material from company 2 Use the same assumptions as in part (a) 10-28.

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The thickness of a plastic lm (in mils) on a substrate material is thought to be in uenced by the temperature at which the coating is applied A completely randomized experiment is carried out Eleven substrates are coated at 125 F, resulting in a sample mean coating thickness of x1 1035 and a sample standard deviation of s1 102 Another 13 substrates are coated at 150 F, for which x2 997 and s2 201 are observed It was originally suspected that raising the process temperature would reduce mean coating thickness Do the data support this claim Use 001 and assume that the two population standard deviations are not equal Calculate an approximate P-value for this test 10-29 Reconsider the coating thickness experiment in Exercise 10-28.

retString = s.ToString() Cache( BuildString ) = retString Else retString = CType(Cache( BuildString ), String) End If Return retString End Function

How could you have answered the question posed regarding the effect of temperature on coating thickness by using a con dence interval Explain your answer 10-30 Reconsider the abrasive wear test in Exercise 10-27 Construct a con dence interval that will address the questions in parts (a) and (c) in that exercise 10-31 The overall distance traveled by a golf ball is tested by hitting the ball with Iron Byron, a mechanical golfer with a swing that is said to emulate the legendary champion, Byron Nelson Ten randomly selected balls of two different brands are tested and the overall distance measured The data follow:.

Let A denote the event that a sample has excellent surface nish, and let B denote the event that a sample has excellent length. If a part is selected at random, determine the following probabilities: (a) P1A2 (b) P1B2 (c) P1A 2 (d) P1A B2 (e) P1A B2 (f) P1A B2 2-47. Samples of emissions from three suppliers are classi ed for conformance to air-quality speci cations. The results from 100 samples are summarized as follows: conforms 1 2 3 yes 22 25 30 no 8 5 10

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