![Bundle: Modern Business Statistics with Microsoft Office Excel, Loose-Leaf Version, 6th + MindTap Business Statistics, 2 terms (12 months) Printed Access Card](https://www.bartleby.com/isbn_cover_images/9781337589383/9781337589383_smallCoverImage.jpg)
Fresno Board Games manufactures and sells several different board games online and through department stores nationwide. Fresno’s most popular game, ¡Cabestrillo Cinco!, is played with 5 six-sided dice. Fresno has purchased dice for this game from Box Cars, Ltd., for twenty-five years, but the company is now considering a move to Big Boss Gaming, Inc. (BBG), a new supplier that has offered to sell dice to Fresno at a substantially lower price. Fresno management is intrigued by the potential savings offered by BBG, but is also concerned about the quality of the dice produced by the new supplier. Fresno has a reputation for high integrity, and its management feels that it is imperative that the dice included with ¡Cabestrillo Cinco! are fair.
To alleviate concerns about the quality of the dice it produces, BBG allows Fresno’s manager of product quality to randomly sample five dice from its most recent production run. While being observed by several members of the BBG management team, Fresno’s manager of product quality rolls each of these five randomly selected dice 500 times and records each outcome. The results for each of these five randomly selected dice are available in the file BBG.
Fresno management now wants to use these data to assess whether any of these five six-sided dice is not fair; that is, does one outcome occur more frequently or less frequently than the other outcomes?
Managerial Report
Prepare a managerial report that addresses the following issues.
- 1. Use
descriptive statistics to summarize the data collected by Fresno’s manager of product quality for each of the five randomly selected dice. Based on these descriptive statistics, what are your preliminary conclusions about the fairness of the five selected dice? - 2. Use the data collected by Fresno’s manager of product quality to test the hypothesis that the first of the five randomly selected dice is fair, i.e., the distribution of outcomes for the first of the five randomly selected dice is multinomial with p1 = p2 = p3 = p4 = p5 = p6 = 1/6. Repeat this process for each of the other four randomly selected dice. Use α = .01. Do the results of your hypothesis tests provide evidence that BBG is producing unfair dice?
![Check Mark](/static/check-mark.png)
Want to see the full answer?
Check out a sample textbook solution![Blurred answer](/static/blurred-answer.jpg)
Chapter 12 Solutions
Bundle: Modern Business Statistics with Microsoft Office Excel, Loose-Leaf Version, 6th + MindTap Business Statistics, 2 terms (12 months) Printed Access Card
- Question 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_forward
- A 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_forwardStem1: 1,4 Stem 2: 2,4,8 Stem3: 2,4 Stem4: 0,1,6,8 Stem5: 0,1,2,3,9 Stem 6: 2,2 What’s the Min,Q1, Med,Q3,Max?arrow_forwardAre the t-statistics here greater than 1.96? What do you conclude? colgPA= 1.39+0.412 hsGPA (.33) (0.094) Find the P valuearrow_forward
- A poll before the elections showed that in a given sample 79% of people vote for candidate C. How many people should be interviewed so that the pollsters can be 99% sure that from 75% to 83% of the population will vote for candidate C? Round your answer to the whole number.arrow_forwardSuppose 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_forward
- A 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_forwardA clinical study is designed to assess the average length of hospital stay of patients who underwent surgery. A preliminary study of a random sample of 70 surgery patients’ records showed that the standard deviation of the lengths of stay of all surgery patients is 7.5 days. How large should a sample to estimate the desired mean to within 1 day at 95% confidence? Round your answer to the whole number.arrow_forwardA clinical study is designed to assess the average length of hospital stay of patients who underwent surgery. A preliminary study of a random sample of 70 surgery patients’ records showed that the standard deviation of the lengths of stay of all surgery patients is 7.5 days. How large should a sample to estimate the desired mean to within 1 day at 95% confidence? Round your answer to the whole number.arrow_forward
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
- Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman
![Text book image](https://www.bartleby.com/isbn_cover_images/9781119256830/9781119256830_smallCoverImage.gif)
![Text book image](https://www.bartleby.com/isbn_cover_images/9781305251809/9781305251809_smallCoverImage.gif)
![Text book image](https://www.bartleby.com/isbn_cover_images/9781305504912/9781305504912_smallCoverImage.gif)
![Text book image](https://www.bartleby.com/isbn_cover_images/9780134683416/9780134683416_smallCoverImage.gif)
![Text book image](https://www.bartleby.com/isbn_cover_images/9781319042578/9781319042578_smallCoverImage.gif)
![Text book image](https://www.bartleby.com/isbn_cover_images/9781319013387/9781319013387_smallCoverImage.gif)