Question

# Test the given claim. Assume that a simple random sample is selected from a normally distributed...

Test the given claim. Assume that a simple random sample is selected from a normally distributed population. Use either the​ P-value method or the traditional method of testing hypotheses. Company A uses a new production method to manufacture aircraft altimeters. A simple random sample of new altimeters resulted in errors listed below. Use a 0.05 level of significance to test the claim that the new production method has errors with a standard deviation greater than 32.2​ ft, which was the standard deviation for the old production method. If it appears that the standard deviation is​ greater, does the new production method appear to be better or worse than the old​ method? Should the company take any​ action? negative 44​, 78​, negative 25​, negative 75​, negative 40​, 13​, 15​, 52​, negative 9​, negative 50​, negative 107​, negative 107 What are the null and alternative​ hypotheses? A. H0​: sigmaequals32.2 ft H1​: sigma not equals32.2 ft B. H0​: sigmaequals32.2 ft H1​: sigma greater than32.2 ft C. H0​: sigma greater than32.2 ft H1​: sigmaequals32.2 ft D. H0​: sigma less than32.2 ft H1​: sigmaequals32.2 ft E. H0​: sigmaequals32.2 ft H1​: sigma less than32.2 ft F. H0​: sigma not equals32.2 ft H1​: sigmaequals32.2 ft Find the test statistic. chi squared equals nothing ​(Round to two decimal places as​ needed.) Determine the critical​ value(s).Since the test statistic is (between,greater, less than or equal to) the critical value, (reject or fail to reject) Ho. There is (sufficient or insufficient) evidence to support the claim that the new production method has errors with a standard deviation greater than 32.2ft. The variation appears to be (about the same, less or greater) than in the past, so the new method appears to be (worse,similar or better), because there will be (the same number of, more or less) altimeters that have errors. Therefore, the company (should or should not) take immediate action to reduce the variation.

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