# Question

Kittlitz (1999) presents data on homicides in Waco, Texas, for the years 1980-1989 (data taken from the Waco Tribune-Herald, December 29, 1989). There were 29 homicides in 1989. Table 6E.15 gives the dates of the 1989 homicides and the number of days between each homicide. The asterisks refer to the fact that two homicides occurred on June 16 and were determined to have occurred 12 hours apart.

a. Plot the days-between-homicides data on a normal probability plot. Does the assumption of a normal distribution seem reasonable for these data?

b. Transform the data using the 0.2777 root of the data. Plot the transformed data on a normal probability plot. Does this plot indicate that the transformation has been successful in making the new data more closely resemble data from a normal distribution?

c. Transform the data using the fourth root (0.25) of the data. Plot the transformed data on a normal probability plot. Does this plot indicate that the transformation has been successful in making the new data resemble more closely data from a normal distribution? Is the plot very different from the one in part (b)?

d. Construct an individual control chart using the transformed data from part (b).

e. Construct an individual control chart using the transformed data from part (c). How similar is it to the one you constructed in part (d)?

f. Is the process stable? Provide a practical interpretation of the control chart.

a. Plot the days-between-homicides data on a normal probability plot. Does the assumption of a normal distribution seem reasonable for these data?

b. Transform the data using the 0.2777 root of the data. Plot the transformed data on a normal probability plot. Does this plot indicate that the transformation has been successful in making the new data more closely resemble data from a normal distribution?

c. Transform the data using the fourth root (0.25) of the data. Plot the transformed data on a normal probability plot. Does this plot indicate that the transformation has been successful in making the new data resemble more closely data from a normal distribution? Is the plot very different from the one in part (b)?

d. Construct an individual control chart using the transformed data from part (b).

e. Construct an individual control chart using the transformed data from part (c). How similar is it to the one you constructed in part (d)?

f. Is the process stable? Provide a practical interpretation of the control chart.

## Answer to relevant Questions

Suggest at least two nonmanufacturing scenarios in which attributes control charts could be useful for process monitoring. Kaminski et al. (1992) present data on the number of orders per truck at a distribution center. Some of this data is shown in Table 6E.19. Set up a c chart for the number of orders per truck. Is the process in control? Draw the type-B OC curve for the single sampling plan n = 50, c = 1. Repeat Exercise 7.16, using general inspection level I. Discuss the differences in the various sampling plans. In exercise 7.16 A lot of 500 items is submitted for inspection. Suppose that we wish to find a plan from MIL STD 414, using inspection level II. If the AQL is 4%, find the Procedure 1 sampling plan from the standard.Post your question

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