Part variability is critical in the manufacturing of ball bearings. Large variances in the size of the ball bearings cause bearing failure and rapid wear-out. Production standards call for a maximum variance of .0001 when the bearing sizes are measured in inches. A sample of 15 bearings shows a sample standard deviation of .014 inches. (i) Use α = .10 to determine whether the sample indicates that the maximum acceptable variance is being exceeded. (ii) Compute the 90% confidence interval estimate of the variance of the ball bearings in the population.
Part variability is critical in the manufacturing of ball bearings. Large variances in the size of the ball bearings cause bearing failure and rapid wear-out. Production standards call for a maximum variance of .0001 when the bearing sizes are measured in inches. A sample of 15 bearings shows a sample standard deviation of .014 inches. (i) Use α = .10 to determine whether the sample indicates that the maximum acceptable variance is being exceeded. (ii) Compute the 90% confidence interval estimate of the variance of the ball bearings in the population.
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Part variability is critical in the manufacturing of ball bearings. Large variances in the size of the ball bearings cause bearing failure and rapid wear-out. Production standards call for a maximum variance of .0001 when the bearing sizes are measured in inches. A sample of 15 bearings shows a sample standard deviation of .014 inches.
(i) Use α = .10 to determine whether the sample indicates that the maximum acceptable variance is being exceeded.
(ii) Compute the 90% confidence
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