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Range charts are used mainly with attribute data.

A) True
B) False

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The chair of the operations management department at Quality University wants to construct a p-chart for determining whether the four faculty teaching the basic P/OM course are under control with regard to the number of students who fail the course. Accordingly, he sampled 100 final grades from last year for each instructor, with the following results:  Instructor  Number of Failures  Prof. A 13 Prof. B 0 Prof. C 11 Prof. D 16\begin{array} { l c } \text { Instructor } & \text { Number of Failures } \\\hline \text { Prof. A } & 13 \\\text { Prof. B } & 0 \\\text { Prof. C } & 11 \\\text { Prof. D } & 16\end{array} What is the estimate of the mean proportion of failures for these instructors?


A) .10
B) .11
C) .13
D) .16
E) .40

F) C) and E)
G) A) and B)

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When a process is not centered, its capability is measured in a slightly different way. The symbol for this case is Cpk.

A) True
B) False

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True

When a process is in control, it results in there being, on average, 16 defects per unit of output. c-chart limits of 4 and 28 would lead to a _______ percent chance of a Type I error.


A) 67
B) 92
C) 33
D) 0.3
E) 5

F) C) and D)
G) B) and C)

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The probability of concluding that assignable variation exists when only random variation is present is: (I) the probability of a Type I error. (II) known as the alpha risk. (III) highly unlikely. (IV) the sum of probabilities in the two tails of the normal distribution.


A) I and II
B) I and IV
C) II and III
D) I, II, and IV
E) I, III, and IV

F) B) and C)
G) C) and D)

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A p-chart would be used to monitor:


A) average shrinkage.
B) dispersion in sample data.
C) the fraction defective.
D) the number of defects per unit.
E) the range of values.

F) C) and D)
G) A) and E)

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The range chart (R-chart) is most likely to detect a change in:


A) proportion.
B) mean.
C) number defective.
D) variability.
E) sample size.

F) A) and D)
G) A) and E)

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A design engineer wants to construct a sample mean chart for controlling the service life of a halogen headlamp his company produces. He knows from numerous previous samples that this service life is normally distributed with a mean of 500 hours and a standard deviation of 20 hours. On three recent production batches, he tested service life on random samples of four headlamps, with these results:  Service Life (hours)   Sample 149550050550025255155055153470480460470\begin{array} { r } { \text { Service Life (hours) } }\\\begin{array} { l l l l l } \text { Sample } & \\\hline 1 & 495 & 500 & 505 & 500 \\2 & 525 & 515 & 505 & 515 \\3 & 470 & 480 & 460 & 470\end{array}\end{array} If he uses upper and lower control limits of 520 and 480 hours, on what sample(s) (if any) does service life appear to be out of control?


A) sample 1
B) sample 2
C) sample 3
D) both samples 2 and 3
E) all samples are in control

F) None of the above
G) C) and D)

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A run test checks a sequence of observations for randomness.

A) True
B) False

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True

A town's department of public works is concerned about adverse public reaction to a sewer project that is currently in progress. Because of this, the commissioner of public works has authorized a weekly survey to be conducted of town residents. Each week, a sample of 100 residents is questioned on their feelings about the project. The results to date are shown below. Analyze these data using control charts that would provide for a 5 percent risk of Type I error.  Week 12345678 Number Opposed 108126414810\begin{array} { l r r r r r r r r } \text { Week } & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 \\\hline \text { Number Opposed } & 10 & 8 & 12 & 6 & 4 & 14 & 8 & 10\end{array}

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Given the following process control data for a quality attribute (three samples of size 400 each):  Sample  Defectives #136#232#352\begin{array} { l r } \text { Sample } & \text { Defectives } \\\hline \# 1 & 36 \\\# 2 & 32 \\\# 3 & 52\end{array} If the process proportion of defectives is unknown, using .10 alpha risk control limits, do any of the sample proportions indicate an out-of-control process proportion of defectives?

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A quality analyst wants to construct a sample mean chart for controlling a packaging process. He knows from past experience that whenever this process is under control, package weight is normally distributed with a mean of 20 ounces and a standard deviation of two ounces. Each day last week, he randomly selected four packages and weighed each:  Weight (ounces)   Day  Monday 23222324 Tuesday 23211921 Wednesday 20192021 Thursday 18192019 Friday 18202220\begin{array} { r } { \text { Weight (ounces) } }\\\begin{array} { l l l l l } \text { Day } \\\hline \text { Monday } & 23 & 22 & 23 & 24 \\\text { Tuesday } & 23 & 21 & 19 & 21 \\\text { Wednesday } & 20 & 19 & 20 & 21 \\\text { Thursday } & 18 & 19 & 20 & 19 \\\text { Friday } & 18 & 20 & 22 & 20\end{array}\end{array} What is the standard deviation of the sampling distribution of sample means for whenever this process is under control?


A) 0.1 ounces
B) 0.4 ounces
C) 0.5 ounces
D) 1 ounce
E) 2 ounces

F) A) and B)
G) C) and D)

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The primary purpose of statistical process control is to detect a defective product before it is shipped to a customer.

A) True
B) False

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Range charts and p-charts are both used for variable data.

A) True
B) False

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Range control charts are used to monitor process central tendency.

A) True
B) False

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The following data occurs chronologically from left to right: 15.219.716.011.114.814.5\begin{array} { l l l l l l } 15.2 & 19.7 & 16.0 & 11.1 & 14.8 & 14.5\end{array} The number of runs up and down is:


A) 2.
B) 3.
C) 4.
D) 5.
E) none of these.

F) A) and E)
G) A) and D)

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The more effective and all-encompassing a firm's quality control and continuous improvement efforts, the less that company will need to rely on:


A) insourcing.
B) inspection.
C) outsourcing.
D) acceptance sampling.
E) capability assessment.

F) A) and D)
G) A) and C)

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B

Organizations should work to improve process capability so that quality control efforts can become more:


A) effective.
B) efficient.
C) necessary.
D) unnecessary.
E) widespread.

F) B) and E)
G) B) and C)

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A process that makes chocolate candy bars has an output that is normally distributed with a mean of 6 ounces and a standard deviation of .01 ounces. A job is to be run that requires 200 candy bars. Determine the three-sigma control limits for an x-bar chart, assuming a sample size of 10. If specifications are 5.98 to 6.02, what run size should be used for this job so that the expected number of good candy bars is 200, assuming the process is in control?

Correct Answer

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A quality analyst wants to construct a control chart for determining whether four machines, all producing the same product, are under control with regard to a particular quality attribute. Accordingly, she inspected 1,000 units of output from each machine in random samples, with the following results:  Machine  Total Defectives #123#215#329#413\begin{array} { l c } \text { Machine } & \text { Total Defectives } \\\hline \# 1 & 23 \\\# 2 & 15 \\\# 3 & 29 \\\# 4 & 13\end{array} What is the sample proportion of defectives for machine #1?


A) .023
B) .02
C) .0115
D) .0058
E) .005

F) All of the above
G) A) and C)

Correct Answer

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