A quality analyst wants to construct a sample mean chart for controlling a packaging process He knows from past experience that the process standard deviation is two ounces Each day last week, he randomly selected four packages and weighed each The data from that activity appear below Weight Day Package 1 Package 2 Package 3 Package 4 Monday 23 22 23 24 Tuesday 23 21 19 21 Wednesday 20 19 20 21 Thursday 18 19 20 19 Friday 18 20 22 20 a What is the mean of all the sample means Select 20 , 20 6 , 23 , 19 b Calculate upper and lower 3 sigma x bar chart control limits that allow for natural variations Select 15 5, 2 4 , 23 6, 17 6 , 20 6, 2 8 , 6 3, 0 c Based on the x bar chart, is this process in control Select cannot be determined , no , maybe , yes

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Question: A quality analyst wants to construct a sample mean chart for controlling a packaging process. He knows from past experience that the process standard deviation

A quality analyst wants to construct a sample mean chart for controlling a packaging process. He knows from past experience that the process standard deviation is two ounces. Each day last week, he randomly selected four packages and weighed each. The data from that activity appear below.

	Weight
Day	Package 1	Package 2	Package 3	Package 4
Monday	23	22	23	24
Tuesday	23	21	19	21
Wednesday	20	19	20	21
Thursday	18	19	20	19
Friday	18	20	22	20

a. What is the mean of all the sample means? [ Select ] ["20", "20.6", "23", "19"]

b. Calculate upper and lower 3-sigma x-bar chart control limits that allow for natural variations. [ Select ] ["15.5, 2.4", "23.6, 17.6", "20.6, 2.8", "6.3, 0"]

c. Based on the x-bar chart, is this process in control? [ Select ] ["cannot be determined", "no", "maybe", "yes"]

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