Q&A Hero

Q: Planning is concerned only with organizational success in the short term, while organizing is concerned with the more distant future (long term).

Q: Planning involves choosing tasks that must be performed to attain organizational goals, outlining how the tasks must be performed, and indicating when they should be performed.

Q: The four basic management functions are planning, organizing, influencing and controlling.

Q: Explain the relationship between control limits and specification limits.

Q: Referring to the SPC chart signals that a process is out of control, what type of problem does each signal indicate? List the signals.

Q: Statistical Process Control charts are used to detect whether a process remains in control or whether it has gone out of control. Explain how the SPC signals work.

Q: Which one of the following is not a source of variation? A) People B) Measurement C) Materials D) Control

Q: A company that fills soft drinks into bottles has established an -chart and an R-chart to monitor the average fill level in the bottles. To do this, the company has taken a series of samples of size n = 4 bottles. The overall average fill is 12.03 ounces. The average range for the subgroups has been .06 ounces. Suppose, after developing the control chart, a subgroup of size 4 yields a sample mean of 12.09 ounces and a range of .08, which of the following statements is true? A) The process is in control on both the -chart and the R-chart. B) The process is out of control on the R-chart but in control on the -chart. C) The process is out of control on the -chart but in control on the R-chart. D) The process is out of control on both the -chart and the R-chart.

Q: A company that fills soft drinks into bottles wishes to establish an -chart to monitor the average fill level in the bottles. To do this, the company has taken a series of samples of size n = 4 bottles. The overall average fill is 12.03 ounces. The average range for the subgroups has been .06 ounces. Based on this information, what is the upper limit of the 3-sigma control limit? A) .729 B) .0437 C) 12.09 D) 12.074

Q: Each evening, a nationwide retail chain randomly calls 100 of the customers who came to their store that day to ask whether they were satisfied with the service they had received. The customers respond yes or no. Suppose the company has found over time that 8 percent of the customers are not satisfied ("no" answers). If they have established a process control chart, what conclusion should be reached if the percentage of customers surveyed tonight that say no is 14 percent? A) This result indicates that a special cause situation exists. B) Although this point is above the upper control limit, there is no cause for alarm if this is the first time. C) While this value is higher than "normal," it is still within the range of common cause variation and no action is needed. D) This is outside the control limits and action should be taken

Q: Recently a shipping company took 30 samples, each of size n = 100, of packages that it was responsible for delivering. Out of the 3,000 total packages, 300 were delivered late. In setting up an appropriate process control chart, what would be the correct 3-sigma upper control limit value? A) 0.03 B) 0.13 C) 0.19 D) 0.07

Q: Which of the following in not an out of control signal for an x-bar chart? A) One or more points outside the control limits B) Seven or more consecutive points that all fall on the same side of the center line C) Six or more consecutive points moving in the same direction (an upward or downward trend) D) Fourteen points in a row, alternating up and down

Q: A plywood manufacturer is interested in monitoring the thickness of the plywood. Which of the following would be most useful for doing this? A) p-charts B) c-charts C) -charts D) Histograms

Q: A p-chart is useful for: A) analyzing whether a process for a measurable variable is in or out of control. B) analyzing processes which yield attribute data. C) determining what the most likely cause of defects is. D) All of the above

Q: The control limits in a control chart can be interpreted to mean: A) any value falling outside the limits is a defect and the product should be discarded. B) the range of virtually all special cause variation. C) any value falling within the limits means the product is high quality. D) the range of virtually all common cause variation.

Q: The main process change that can be detected with a process control chart is: A) the process average has shifted up or down from normal. B) the process average is trending up or down from normal. C) the process is behaving in such a manner that the existing variation is not random in nature. D) All of the above

Q: Which of the following statements is correct? A) A process can be in statistical control, yet it can be producing defects in abundance. B) At least three points outside the upper or lower control limits on a control chart are required before the process is deemed to be out of control. C) If a process is out of control, then the variation that is present is limited to common cause variation. D) When special cause variation is present, the process can be expected to be in control.

Q: Which of the following is not a type of commonly used process control chart? A) x-bar chart B) R-chart C) p-chart D) n-chart

Q: The x-bar chart is based on the principles of which distribution? A) t-distribution B) Chi square distribution C) F distribution D) Normal distribution

Q: Which of the following is not among the most common sources of variation? A) People B) Materials C) Methods D) Quotas

Q: When discussing variation in the output of a process, which of the following is not true? A) Variation is natural. B) No two products or services are exactly the same. C) With a fine enough measurement gauge, all things can be seen to differ. D) Common cause variation can be eliminated.

Q: Because variations are unavoidable in a system, the output of the system is always unpredictable.

Q: The statistical process control (SPC) chart is one of the most important tools for identifying important issues to improve quality.

Q: A process control chart can be used to determine whether the process average has shifted up or down, but is not useful for determining whether the process is just drifting in an upward or downward direction.

Q: In most processes, the process control limits are set to correspond with the specification limits on the product.

Q: One of the roles of managers who are overseeing the statistical process control analysis is to set the control limits at the desired levels prior to collecting data from the process.

Q: The control limits in the x-bar chart are set so that 95 percent of the values will fall inside the control limits when there is only common cause variation.

Q: It is entirely possible for the R-chart to show that a process is in statistical control and the -chart to show that the same process is out of control.

Q: The frequency distribution of most processes' statistics will begin to resemble the shape of the normal distribution as the values are collected and grouped into classes.

Q: Both p-charts and c-charts are designed for use when the data we are working with are referred to as attribute data.

Q: A p-chart would potentially be used to monitor the diameters of bolts made by a bolt manufacturing plant.

Q: A stable process is typically defined as one in which all output is operating within 3 standard deviations of the process center.

Q: A stable process is one that has had all its variation removed through quality improvement efforts on the part of the organization.

Q: Total process variation is made up of the sum of common cause variation and special cause variation.

Q: One of the most common sources of common cause variation is the people who are working in the process.

Q: If a process control chart has only one point outside the upper or lower control limits, there is insufficient evidence to conclude that the process was out of control at the time that the measurement was taken.

Q: Process control charts are used to provide signals to indicate when the output of a process is out of control.

Q: The six most common sources of variation are people, machines, materials, methods, measurement, and environment.

Q: In process improvement efforts, the goal is to first remove the common cause variation and then to reduce the special cause variation in a system.

Q: Common cause variation is variation in the output of a process that is unexpected and has an assignable cause.

Q: Special cause variation is variation in the output of a process that is naturally occurring and expected and that may be the result of random causes.

Q: Variation exists naturally in the world around us so all processes and products can be expected to vary.

Q: We expect virtually all the data in a stable process to fall within 2 standard deviations of the mean.

Q: Business Statistics, 9e (Groebner/Shannon/Fry)

Q: Nonparametric statistical tests are used when: A) the sample sizes are small. B) we are unwilling to make the assumptions of parametric tests. C) the standard normal distribution cannot be computed. D) the population parameters are unknown.

Q: If you are interested in testing whether the median of a population is equal to a specific value, an appropriate test to use is: A) the Mann-Whitney U test. B) the t-test. C) the Wilcoxon signed rank test. D) the Wilcoxon Matched-Pairs Signed Rank test.

Q: Kruskal-Wallis One-Way Analysis of Variance is the nonparametric counterpart to the one-way ANOVA procedure in which the assumptions of normally distributed populations with equal variances are satisfied.

Q: The makers of furnace filters recently conducted a test to determine whether the median number of particulates that would pass through their four leading filters was the same. A random sample of 6 of each type of filter was used with the following data being recorded: Filter 1 Filter 2 Filter 3 Filter 4 40 100 165 55 25 110 90 20 70 89 40 90 47 67 200 105 55 77 103 90 88 102 110 120 If the Kruskal-Wallis test is used with an alpha = .01, the null hypothesis should be rejected and the managers should conclude that the four filters do not allow an equal median number of particulates.

Q: Assume that a Kruskal-Wallis test is being conducted to determine whether or not the medians of three populations are equal. The sum of rankings and the sample size for each group are below. Group 1 Group 2 Group 3 R1= 60 R2= 36 R3= 24 n1= 6 n2= 5 n3= 4 The value of the test statistic is H = 0.68

Q: A recent study was conducted to determine if any of three suppliers of electronic components has a different median delivery time on special orders. To test this, five orders were given to each supplier and the delivery days were recorded. These data are shown as follows: Supplier 1 Supplier 2 Supplier 3 15 11 15 19 7 9 13 19 5 10 10 12 20 12 10 If a Kruskal-Wallis test is to be performed, the sum of the rankings for Supplier 1 is 45.

Q: The critical value for a Kruskal Wallis test is an F value from the F-distribution.

Q: In using the Kruskal-Wallis test the sample sizes for each population must be equal.

Q: The Kruskal-Wallis test is used to test whether the centers of 3 or more populations are equal so long as that is the only possible difference between the population distributions.

Q: The distribution of T-values in the Wilcoxon Matched-Pairs Signed Rank test is approximately normal if the sample size (number of matched pairs) exceeds 25.

Q: When testing whether two paired populations have equal medians and the sample sizes are large, it is appropriate to convert the Wilcoxon Matched-Pairs Signed Rank test to a paired sample t-test.

Q: In conducting the Wilcoxon Matched-Pairs Signed Rank test, the difference between each pair of values must be found prior to conducting any ranking.

Q: In order to determine whether the median distance for the X-Special golf ball exceeds the median distance for the best-selling golf ball, six golfers were selected and asked to hit each ball with their driver. The distance was recorded. The following data were observed. Golfer X-Special Best Seller 1 240 233 2 267 270 3 255 240 4 234 230 5 250 260 6 285 270 Based on these data, and testing at an alpha = 0.025 level, the critical value for the Wilcoxon Matched Pairs Signed Rank test is 2.

Q: One of the assumptions associated with the Wilcoxon Matched-Pairs Signed Rank test is that the distribution of the population differences is symmetric about their median.

Q: The Wilcoxon Matched-Pairs Signed rank test is an alternative to the paired sample t-test when we are unwilling to assume that the populations are normally distributed.

Q: If a decision maker wishes to test to determine whether the medians are equal for two populations the Mann-Whitney U test is appropriate for either independent or dependent sampling situations.

Q: A large sample Mann-Whitney U test should be used when the sample sizes exceed 20.

Q: In conducting a Mann-Whitney U test when the sample size is greater than 20, the U test statistic can be assumed normally distributed.

Q: Recently, a study was done to determine whether the median speed on a section of highway is the same for cars versus trucks. A sample of 12 cars (n1= 12) and 15 trucks (n2= 15) was collected. If the Mann-Whitney U test is to be performed using an alpha = .05 and if the U test statistic is calculated to be 68, the null hypothesis should be rejected.

Q: A claim was recently made that stated that the median income for male and female graduates is the same for those graduating with a degree in operations management. The following sample data were collected: Males Females $42,000 $39,000 $36,000 $39,000 $40,000 $41,000 $32,000 $42,000 $50,000 $44,000 $47,000 $38,000 $47,000 $51,000 In employing the Mann-Whitney U test, the U test statistic is 25.5

Q: The critical value for a one-tailed Mann-Whitney U test with sample sizes of n1= 10 and n2= 10 is 23 for a 0.05 level of significance.

Q: The Mann-Whitney U test is always a one-tailed test.

Q: In a Mann-Whitney U test, if the sample sizes are large then the test statistic can be approximated by the student's t-distribution.

Q: In a Mann-Whitney U test, the test statistic will be equal to the sum of the ranks from sample one, or sample two, whichever is larger.

Q: One of the assumptions of the Mann-Whitney U test is that the population distributions are the same for shape and spread.

Q: The logic behind the Mann-Whitney U test is that if the hypothesis is true that the populations have equal central locations, then the sum of the ranks from each population will be approximately equal.

Q: In employing the Mann-Whitney U test, the sample data from the two populations are first combined and the ranks of the data are determined, but we keep track of which population each ranked item came from.

Q: The Mann-Whitney U test can be used to test whether two independent populations have the same median so long as the data are measured on at least an ordinal scale.

Q: The Mann-Whitney U test is a nonparametric test that is used to test whether two related populations have the same median.

Q: The procedure of the Wilcoxon signed rank test is the same for either small or large sample sizes.

Q: In a large sample test about a single population median, it is appropriate to employ the standard normal distribution so long as the population is also normally distributed.

Q: In the Wilcoxon signed rank test using either small or large sample sizes, any value that equals the hypothesized median is discarded from the analysis.

Q: In the Wilcoxon signed rank test for testing about a single population median, if the sample size is large (n > 20), the test statistic can be approximated by the standard normal distribution.

Q: In conducting the Wilcoxon signed rank test, after collecting the sample data the next step is to find the sample median and subtract this value from each data value to obtain the deviations.

Q: Managers for a company that produces a weight loss product claim that the median weight lost over six weeks for people who use this product will be at least 20 pounds. The following data were collected from a sample of nine people who used the product. Pounds Lost 6.00 22.00 14.00 5.00 30.00 12.00 7.00 21.00 25.00 Based on these data, the test statistic is W = 12.

Q: Recently, Major League Baseball officials stated that the median cost for a family of four to attend a baseball game including, parking, tickets, food, and drinks did not exceed $125.00. The following sample data were collected: Dollars Spent 142.00 99.00 134.00 175.00 100.00 225.00 80.00 Assuming that the test of the owners' claim is going to be conducted using an alpha = .05 level, the null hypothesis that the median cost does not exceed $125 should not be rejected.