Applied Statistics and Probability for Engineers
6th Edition
ISBN: 9781118539712
Author: Douglas C. Montgomery
Publisher: WILEY
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Chapter 6.2, Problem 25E
a.
To determine
Construct a stem-and-leaf diagram.
b.
To determine
Check whether any of the bridges appear to have unusually good or poor ratings.
c.
To determine
Derive the
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A marketing professor has surveyed the students at her university to better understand attitudes towards PPT usage for higher education. To be able to make inferences to the entire student body, the sample drawn needs to represent the university’s student population on all key characteristics. The table below shows the five key student demographic variables. The professor found the breakdown of the overall student body in the university’s fact book posted online.
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What were the average sales for the standard POP display (control group)?
What were the sales for the digital display (experimental group)?
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Chapter 6 Solutions
Applied Statistics and Probability for Engineers
Ch. 6.1 - 6-1. Will the sample mean always correspond to one...Ch. 6.1 - 6-2. Will exactly half of the observations in a...Ch. 6.1 - Prob. 3ECh. 6.1 - 6-4. For any set of data values, is it possible...Ch. 6.1 - 6-5. Can the sample standard deviation be equal to...Ch. 6.1 - 6-6. Suppose that you add 10 to all of the...Ch. 6.1 - 6-7. Eight measurements were made on the inside...Ch. 6.1 - Prob. 8ECh. 6.1 - Prob. 9ECh. 6.1 - 6-10. An article in the Journal of Structural...
Ch. 6.1 - Prob. 11ECh. 6.1 - Prob. 12ECh. 6.1 - Prob. 13ECh. 6.1 - 6-14. Preventing fatigue crack propagation in...Ch. 6.1 - 6-15. An article in the Journal of Physiology...Ch. 6.1 - Prob. 16ECh. 6.1 - 6-17. The pH of a solution is measured eight times...Ch. 6.1 - Prob. 18ECh. 6.1 - Prob. 19ECh. 6.1 - Prob. 20ECh. 6.1 - Prob. 21ECh. 6.1 - 6-22. Cloud seeding, a process in which chemicals...Ch. 6.1 - Prob. 23ECh. 6.1 - Prob. 24ECh. 6.2 - 6-25. For the data in Exercise 6-20,
(a) Construct...Ch. 6.2 - 6-26. For the data in Exercise 6-21,
(a) Construct...Ch. 6.2 - Prob. 27ECh. 6.2 - Prob. 28ECh. 6.2 - Prob. 29ECh. 6.2 - 6-30. An article in Technometrics (1977, Vol. 19,...Ch. 6.2 - 6-31. Go Tutorial The following data are the...Ch. 6.2 - Prob. 32ECh. 6.2 - 6-33. The following data represent the yield on 90...Ch. 6.2 - 6-34. Calculate the sample median, mode, and mean...Ch. 6.2 - Prob. 35ECh. 6.2 - Prob. 36ECh. 6.2 - Prob. 37ECh. 6.2 - Prob. 38ECh. 6.2 - Prob. 39ECh. 6.2 - 6-40. An important quality characteristic of water...Ch. 6.2 - Prob. 41ECh. 6.2 - 6-42. A semiconductor manufacturer produces...Ch. 6.2 - Prob. 43ECh. 6.2 - 6-44. In their book Introduction to Linear...Ch. 6.2 - Prob. 45ECh. 6.3 - 6-46. Construct a frequency distribution and...Ch. 6.3 - 6-47. Construct a frequency distribution and...Ch. 6.3 - 6-48. Construct a frequency distribution and...Ch. 6.3 - Prob. 49ECh. 6.3 - 6-50. Construct frequency distributions and...Ch. 6.3 - 6-51. Construct histograms with 8 and 16 bins for...Ch. 6.3 - 6-52. Construct histograms with 8 and 16 bins for...Ch. 6.3 - Prob. 53ECh. 6.3 - 6-54. Construct a histogram for the female student...Ch. 6.3 - 6-55. Construct a histogram for the spot weld...Ch. 6.3 - 6-56. Construct a histogram for the water quality...Ch. 6.3 - Prob. 57ECh. 6.3 - Prob. 58ECh. 6.3 - 6-59. Construct a histogram for the pinot noir...Ch. 6.3 - Prob. 60ECh. 6.3 - Prob. 61ECh. 6.3 - Prob. 62ECh. 6.3 - 6-63. Construct a frequency distribution and...Ch. 6.3 - Prob. 64ECh. 6.4 - 6-65. Using the data on bridge conditions from...Ch. 6.4 - 6-66. Using the data on acid rain from Exercise...Ch. 6.4 - 6-67. Using the data from Exercise 6-22 on cloud...Ch. 6.4 - 6-68. Using the data from Exercise 6-24 on swim...Ch. 6.4 - Prob. 69ECh. 6.4 - Prob. 70ECh. 6.4 - 6-71. The nine measurements that follow are...Ch. 6.4 - Prob. 72ECh. 6.4 - Prob. 73ECh. 6.4 - Prob. 75ECh. 6.4 - Prob. 76ECh. 6.4 - Prob. 77ECh. 6.4 - Prob. 78ECh. 6.4 - Prob. 79ECh. 6.4 - 6-80 In Exercise 6-69, data were presented on the...Ch. 6.4 - 6-81. An article in Nature Genetics...Ch. 6.5 - 6-82. The following data are the viscosity...Ch. 6.5 - Prob. 83ECh. 6.5 - 6-84. In their book Time Series Analysis,...Ch. 6.5 - Prob. 85ECh. 6.5 - Prob. 86ECh. 6.5 - Prob. 87ECh. 6.5 - Prob. 88ECh. 6.5 - Prob. 89ECh. 6.6 - Prob. 90ECh. 6.6 - Prob. 91ECh. 6.6 - 6-92. An article in the Journal of Pharmaceuticals...Ch. 6.7 - 6-93. Construct a normal probability plot of the...Ch. 6.7 - 6-94. Construct a normal probability plot of the...Ch. 6.7 - Prob. 95ECh. 6.7 - 6-96. Construct a normal probability plot of the...Ch. 6.7 - Prob. 97ECh. 6.7 - 6-98. Construct a normal probability plot of the...Ch. 6.7 - Prob. 99ECh. 6.7 - 6-100. Construct a normal probability plot of the...Ch. 6.7 - Prob. 101ECh. 6.7 - Prob. 102ECh. 6 - Prob. 103SECh. 6 - 6-104. The concentration of a solution is measured...Ch. 6 - 6-105. Table 6E.10 shows unemployment data for the...Ch. 6 - 6-106. A sample of six resistors yielded the...Ch. 6 - 6-107. Consider the following two samples:
Sample...Ch. 6 - 6-108. An article in Quality Engineering (1992....Ch. 6 - Prob. 109SECh. 6 - Prob. 110SECh. 6 - Prob. 111SECh. 6 - Prob. 112SECh. 6 - 6-113. Q A manufacturer of coil springs is...Ch. 6 - 6-114. A communication channel is being monitored...Ch. 6 - Prob. 115SECh. 6 - Prob. 116SECh. 6 - 6-117. Construct a normal probability plot of the...Ch. 6 - Prob. 118SECh. 6 - Prob. 119SECh. 6 - Prob. 120SECh. 6 - Prob. 121SECh. 6 - 6-122. In 1789, Henry Cavendish estimated the...Ch. 6 - Prob. 123SECh. 6 - 6-124. Patients arriving at a hospital emergency...Ch. 6 - Prob. 125SECh. 6 - 6-126. The energy consumption for 90 gas-heated...Ch. 6 - Prob. 127SECh. 6 - Prob. 128SECh. 6 - Prob. 129SECh. 6 - Prob. 130SECh. 6 - Prob. 131SECh. 6 - Prob. 132SECh. 6 - Prob. 133SECh. 6 - Prob. 134SECh. 6 - Prob. 135SECh. 6 - Prob. 136SECh. 6 - Prob. 137SE
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- What were the average sales for the four weeks prior to the experiment? What were the sales during the four weeks when the stores used the digital display? What is the mean difference in sales between the experimental and regular POP time periods? State the null hypothesis being tested by the paired sample t-test. Do you reject or retain the null hypothesis? At a 95% significance level, was the difference significant? Explain why or why not using the results from the paired sample t-test. Should the manager of the retail chain install new digital displays in each store? Justify your answer.arrow_forwardA retail chain is interested in determining whether a digital video point-of-purchase (POP) display would stimulate higher sales for a brand advertised compared to the standard cardboard point-of-purchase display. To test this, a one-shot static group design experiment was conducted over a four-week period in 100 different stores. Fifty stores were randomly assigned to the control treatment (standard display) and the other 50 stores were randomly assigned to the experimental treatment (digital display). Compare the sales of the control group (standard POP) to the experimental group (digital POP). What were the average sales for the standard POP display (control group)? What were the sales for the digital display (experimental group)? What is the (mean) difference in sales between the experimental group and control group? List the null hypothesis being tested. Do you reject or retain the null hypothesis based on the results of the independent t-test? Was the difference between the…arrow_forwardQuestion 4 An article in Quality Progress (May 2011, pp. 42-48) describes the use of factorial experiments to improve a silver powder production process. This product is used in conductive pastes to manufacture a wide variety of products ranging from silicon wafers to elastic membrane switches. Powder density (g/cm²) and surface area (cm/g) are the two critical characteristics of this product. The experiments involved three factors: reaction temperature, ammonium percentage, stirring rate. Each of these factors had two levels, and the design was replicated twice. The design is shown in Table 3. A222222222222233 Stir Rate (RPM) Ammonium (%) Table 3: Silver Powder Experiment from Exercise 13.23 Temperature (°C) Density Surface Area 100 8 14.68 0.40 100 8 15.18 0.43 30 100 8 15.12 0.42 30 100 17.48 0.41 150 7.54 0.69 150 8 6.66 0.67 30 150 8 12.46 0.52 30 150 8 12.62 0.36 100 40 10.95 0.58 100 40 17.68 0.43 30 100 40 12.65 0.57 30 100 40 15.96 0.54 150 40 8.03 0.68 150 40 8.84 0.75 30 150…arrow_forward
- - + ++ Table 2: Crack Experiment for Exercise 2 A B C D Treatment Combination (1) Replicate I II 7.037 6.376 14.707 15.219 |++++ 1 བྱ॰༤༠སྦྱོ སྦྱོཋཏྟཱུ a b ab 11.635 12.089 17.273 17.815 с ас 10.403 10.151 4.368 4.098 bc abc 9.360 9.253 13.440 12.923 d 8.561 8.951 ad 16.867 17.052 bd 13.876 13.658 abd 19.824 19.639 cd 11.846 12.337 acd 6.125 5.904 bcd 11.190 10.935 abcd 15.653 15.053 Question 3 Continuation of Exercise 2. One of the variables in the experiment described in Exercise 2, heat treatment method (C), is a categorical variable. Assume that the remaining factors are continuous. (a) Write two regression models for predicting crack length, one for each level of the heat treatment method variable. What differences, if any, do you notice in these two equations? (b) Generate appropriate response surface contour plots for the two regression models in part (a). (c) What set of conditions would you recommend for the factors A, B, and D if you use heat treatment method C = +? (d) Repeat…arrow_forwardQuestion 2 A nickel-titanium alloy is used to make components for jet turbine aircraft engines. Cracking is a potentially serious problem in the final part because it can lead to nonrecoverable failure. A test is run at the parts producer to determine the effect of four factors on cracks. The four factors are: pouring temperature (A), titanium content (B), heat treatment method (C), amount of grain refiner used (D). Two replicates of a 24 design are run, and the length of crack (in mm x10-2) induced in a sample coupon subjected to a standard test is measured. The data are shown in Table 2. 1 (a) Estimate the factor effects. Which factor effects appear to be large? (b) Conduct an analysis of variance. Do any of the factors affect cracking? Use a = 0.05. (c) Write down a regression model that can be used to predict crack length as a function of the significant main effects and interactions you have identified in part (b). (d) Analyze the residuals from this experiment. (e) Is there an…arrow_forwardA 24-1 design has been used to investigate the effect of four factors on the resistivity of a silicon wafer. The data from this experiment are shown in Table 4. Table 4: Resistivity Experiment for Exercise 5 Run A B с D Resistivity 1 23 2 3 4 5 6 7 8 9 10 11 12 I+I+I+I+Oooo 0 0 ||++TI++o000 33.2 4.6 31.2 9.6 40.6 162.4 39.4 158.6 63.4 62.6 58.7 0 0 60.9 3 (a) Estimate the factor effects. Plot the effect estimates on a normal probability scale. (b) Identify a tentative model for this process. Fit the model and test for curvature. (c) Plot the residuals from the model in part (b) versus the predicted resistivity. Is there any indication on this plot of model inadequacy? (d) Construct a normal probability plot of the residuals. Is there any reason to doubt the validity of the normality assumption?arrow_forward
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- Suppose a random sample of 459 married couples found that 307 had two or more personality preferences in common. In another random sample of 471 married couples, it was found that only 31 had no preferences in common. Let p1 be the population proportion of all married couples who have two or more personality preferences in common. Let p2 be the population proportion of all married couples who have no personality preferences in common. Find a95% confidence interval for . Round your answer to three decimal places.arrow_forwardA history teacher interviewed a random sample of 80 students about their preferences in learning activities outside of school and whether they are considering watching a historical movie at the cinema. 69 answered that they would like to go to the cinema. Let p represent the proportion of students who want to watch a historical movie. Determine the maximal margin of error. Use α = 0.05. Round your answer to three decimal places. arrow_forwardA random sample of medical files is used to estimate the proportion p of all people who have blood type B. If you have no preliminary estimate for p, how many medical files should you include in a random sample in order to be 99% sure that the point estimate will be within a distance of 0.07 from p? Round your answer to the next higher whole number.arrow_forward
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