In the manufacture of machinery, it is essential to utilize parts that conform to specifications. In the past, diameters of the ball bearings produced by Kruger Industrial Smoothing had a standard deviation of 0.0395 mm. To cut costs, you as a quality engineer instituted a less expensive production method. The diameters (in mm) of a sample of 50 ball bearings collected after the new production method are found in below as "DATA". Do the data provide sufficient evidence to indicate that diameters of ball bearings produced by the new process are more variable than those produced by the old process? Test at ? = 0.05. a. Use the ?-value approach using the tables in the book. (Book Statistics For Engineering And The Sciences, Sixth Edition) b. Use the ?-value approach using Excel. DATA: 10.04337 9.95573 10.01484 9.94373 10.022 10.02316 10.02519 10.02941 10.02013 10.06552 10.01739 9.99704 10.04592 9.98853 9.99617 9.98865 9.93464 9.91009 10.01019 10.15476 10.04858 9.96005 9.95594 9.96715 9.95727 9.99519 10.01184 9.9465 9.95369 9.96279 9.92677 10.00159 10.00884 10.03298 10.03077 10.01959 9.99353 9.97688 10.03936 9.98908 9.97663 9.94476 10.00159 9.97672 9.9618 10.0057 10.04001 10.00094 10.03854 10.09998

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Problem 6
In the manufacture of machinery, it is essential to utilize parts that conform to specifications. In
the past, diameters of the ball bearings produced by Kruger Industrial Smoothing had a
standard deviation of 0.0395 mm. To cut costs, you as a quality engineer instituted a less
expensive production method. The diameters (in mm) of a sample of 50 ball bearings collected
after the new production method are found in below as "DATA". Do the data provide
sufficient evidence to indicate that diameters of ball bearings produced by the new process are
more variable than those produced by the old process? Test at ? = 0.05.


a. Use the ?-value approach using the tables in the book. (Book Statistics For Engineering And The Sciences, Sixth Edition)
b. Use the ?-value approach using Excel.

DATA:

10.04337
9.95573
10.01484
9.94373
10.022
10.02316
10.02519
10.02941
10.02013
10.06552
10.01739
9.99704
10.04592
9.98853
9.99617
9.98865
9.93464
9.91009
10.01019
10.15476
10.04858
9.96005
9.95594
9.96715
9.95727
9.99519
10.01184
9.9465
9.95369
9.96279
9.92677
10.00159
10.00884
10.03298
10.03077
10.01959
9.99353
9.97688
10.03936
9.98908
9.97663
9.94476
10.00159
9.97672
9.9618
10.0057
10.04001
10.00094
10.03854
10.09998
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