anufacturer produces, packages, and sells packs of their product targeted to weigh 50 grams. A quality trol manager working for the company was concerned that the variation in the actual weights of the geted 50-gram packs was larger than acceptable. That is, he was concerned that some packs weighed nificantly less than 50-grams and some weighed significantly more than 50 grams. In an attempt to imate the standard deviation of the weights of all of the 50-gram packs the manufacturer makes, he k a random sample of 21 packs off of the factory line. The random sample yielded the sample mean 86 grams and the standard deviation of 0.655 grams. Use the random sample to derive a 99% confidenc erval for the variance (standard deviation) of the actual weights of the packs. e: if the normality plot is not provided you may assume that the actual weights of the packs are mally distributed. i. Procedure: Select an answer Select an answer One mean Z procedure One variance x² procedure One mean T procedure One proportion Z procedure ii. Assumptions: (select everything that applies) Simple random sample The number of positive and negative responses are both greater than 10

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Author:Amos Gilat
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Question 6
A manufacturer produces, packages, and sells packs of their product targeted to weigh 50 grams. A quality
control manager working for the company was concerned that the variation in the actual weights of the
targeted 50-gram packs was larger than acceptable. That is, he was concerned that some packs weighed
significantly less than 50-grams and some weighed significantly more than 50 grams. In an attempt to
estimate the standard deviation of the weights of all of the 50-gram packs the manufacturer makes, he
took a random sample of 21 packs off of the factory line. The random sample yielded the sample mean
49.86 grams and the standard deviation of 0.655 grams. Use the random sample to derive a 99% confidence
interval for the variance (standard deviation) of the actual weights of the packs.
Note: if the normality plot is not provided you may assume that the actual weights of the packs are
normally distributed.
i. Procedure:
Select an answer
Select an answer
One mean Z procedure
One variance x² procedure
One mean T procedure
One proportion Z procedure
ii. Assumptions: (select everything that applies)
Simple random sample
The number of positive and negative responses are both greater than 10
Population standard deviation is unknown
Sample size is greater than 30
Normal population
O Population standard deviation is known
iii. Unknown parameter: Select an answer
Select an answer
p, population proportion
μ, population mean
o², population variance
Transcribed Image Text:Question 6 A manufacturer produces, packages, and sells packs of their product targeted to weigh 50 grams. A quality control manager working for the company was concerned that the variation in the actual weights of the targeted 50-gram packs was larger than acceptable. That is, he was concerned that some packs weighed significantly less than 50-grams and some weighed significantly more than 50 grams. In an attempt to estimate the standard deviation of the weights of all of the 50-gram packs the manufacturer makes, he took a random sample of 21 packs off of the factory line. The random sample yielded the sample mean 49.86 grams and the standard deviation of 0.655 grams. Use the random sample to derive a 99% confidence interval for the variance (standard deviation) of the actual weights of the packs. Note: if the normality plot is not provided you may assume that the actual weights of the packs are normally distributed. i. Procedure: Select an answer Select an answer One mean Z procedure One variance x² procedure One mean T procedure One proportion Z procedure ii. Assumptions: (select everything that applies) Simple random sample The number of positive and negative responses are both greater than 10 Population standard deviation is unknown Sample size is greater than 30 Normal population O Population standard deviation is known iii. Unknown parameter: Select an answer Select an answer p, population proportion μ, population mean o², population variance
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