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Engineering: Cracks Henry Petroski is a professor of civil engineering at Duke University. In his book To Engineer Is Human: The Role of Failure in Successful Design, Professor Petroski says that up to 95% of all structural failures, including those of bridges, airplanes, and other commonplace products of technology, are believed to be the result of crack growth. In most cases, the cracks grow slowly. It is only when the cracks reach intolerable proportions and still go undetected that catastrophe can occur. In a cement retaining wall, occasional hairline cracks are normal and nothing to worry about. If these cracks are spread out and not too close together, the wall is considered safe. However, if a number of cracks group together in a small region, there may be real trouble. Suppose a given cement retaining wall is considered safe if hairline cracks are evenly spread out and occur on the average of 4.2 cracks per 30-foot section of wall.
- (a) Explain why a Poisson
probability distribution would be a good choice for the random variable r = number of hairline cracks for a given length of retaining wall. - (b) In a 50-foot section of safe wall, what is the probability of three (evenly spread-out) hairline cracks? What is the probability of three or more (evenly spread-out) hairline cracks?
- (c) Answer part (b) for a 20-foot section of wall.
- (d) Answer part (b) for a 2-foot section of wall. Round λ to the nearest tenth.
- (e) Consider your answers to parts (b), (c), and (d). If you had three hairline cracks evenly spread out over a 50-foot section of wall, should this be cause for concern? The probability is low. Could this mean that you are lucky to have so few cracks? On a 20-foot section of wall [part (c)], the probability of three cracks is higher. Does this mean that this distribution of cracks is closer to what we should expect? For part (d), the probability is very small. Could this mean you are not so lucky and have something to worry about? Explain your answers.
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Chapter 5 Solutions
Bundle: Understandable Statistics: Concepts And Methods, 12th + Jmp Printed Access Card For Peck's Statistics + Webassign Printed Access Card For ... And Methods, 12th Edition, Single-term
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- Question 1 A tech company has acknowledged the importance of having records of all meetings conducted. The meetings are very fast paced and requires equipment that is able to capture the information in the shortest possible time. There are two options, using a typewriter or a word processor. Fifteen administrative assistants are selected and the amount of typing time in hours was recorded. The results are given below: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 typewriter 8.0 6.5 5.0 6.7 7.8 8.5 7.2 5.7 9.2 5.7 6.5 word processor 7.2 5.7 8.3 7.5 9.2 7.2 6.5 7.0 6.9 34 7.0 6.9 8.8 6.7 8.8 9.4 8.6 5.5 7.2 8.4 a. Test the hypothesis that the mean typing time in hours for typewriters is less than 7.0. Use the 1% level of significance. b. Construct a 90% confidence interval for the difference in mean typing time in hours, where a difference is equal to the typing time in hours of word processors minus typing time in hours of typewriter. c. Using the 5% significance level, determine whether there is…arrow_forwardIllustrate 2/7×4/5 using a rectangular region. Explain your work. arrow_forwardWrite three other different proportions equivalent to the following using the same values as in the given proportion 3 foot over 1 yard equals X feet over 5 yardsarrow_forward
- 2. An experiment is set up to test the effectiveness of a new drug for balancing people's mood. The table below contains the results of the patients before and after taking the drug. The possible scores are the integers from 0 to 10, where 0 indicates a depressed mood and 10 indicates and elated mood. Patient Before After 1 4 4 2 3 3 3 6 4 4 1 2 5 6 5 6 1 3 7 4 7 8 6 9 1 4 10 5 4 Assuming the differences of the observations to be symmetric, but not normally distributed, investigate the effectiveness of the drug at the 5% significance level. [4 Marks]arrow_forward3. (i) Consider the following R code: wilcox.test(UK Supermarkets $Salary ~ UKSupermarkets $Supermarket) (a) Which test is being used in this code? (b) What is the name of the dataset under consideration? How would be adapt this code if we had ties? What other command can be used which deals with ties? (ii) Consider the following R code: install packages("nortest") library(nortest) lillie.test (Differences) (a) Assuming the appropriate dataset has been imported and attached, what is wrong with this code? (b) If this code were to be corrected, what would be determined by run- ning it? [3 Marks]arrow_forward1. (i) Explain the difference in application between the Mann-Whitney U test and the Wilcoxon Signed-Rank test, i.e. in which scenarios would each test be used? (ii) What is the main procedure underlying these nonparametric tests? [3 Marks]arrow_forward
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