# Quant Quant and more Quant!

1. The quality-control manager at a light bulb factory needs to determine whether the mean life of a large shipment of light bulbs is equal to 375 hours. The population standard deviation is 100 hours. A random sample of 64 light bulbs indicates a sample mean life of 350 hours.

a. At the 0.05 level of significance, is there evidence that the mean life is different from 375 hours?

b. Compute the p-value and interpret its meaning.

c. Construct a 95% confidence interval estimate of the population mean life of the light bulbs.

d. Compare the results of (a) and ©. What conclusions do you reach?

1. Southside Hospital in Bay Shore, New York, commonly conducts stress tests to study the heart muscle after a person has a heart attack. Members of the diagnostic imaging department conducted a quality improvement project with the objective of reducing the turnaround time for stress tests. Turnaround time is defined as the time from when a test is ordered to when the radiologist signs off on the test results. Initially, the mean turnaround time for a stress test was 68 hours. After incorporating changes into the stress-test process, the quality improvement team collected a sample of 50 turnaround times. In this sample, the mean turnaround time was 32 hours, with a standard deviation of 9 hours. (Data extracted from E. Godin, D. Raven, C. Sweetapple, and F. R. Del Guidice, “Faster Test Results,” Quality Progress, January 2004, 37(1), pp. 33–39.)

a. If you test the null hypothesis at the 0.01 level of significance, is there evidence that the new process has reduced turnaround time?

b. Interpret the meaning of the p-value in this problem.

1. The U.S. Department of Education reports that 46% of full-time college students are employed while attending college. (Data extracted from “The Condition of Education 2009,” National Center for Education Statistics, nces.ed. gov.) A recent survey of 60 full-time students at Miami University found that 29 were employed.

a. Use the five-step p-value approach to hypothesis testing and a 0.05 level of significance to determine whether the proportion of full-time students at Miami University is different from the national norm of 0.46.

b. Assume that the study found that 36 of the 60 full-time students were employed and repeat (a). Are the conclusions the same?

Wowzer!

I’d encourage you to put these in separate threads. It’ll be too confusing otherwise.

^ It would be a good exercise for those who’ve masted their way through populations, standard deviations, Z/T Tables, and Hypothesis Testing + P Values.

Help my boy out! Good people helping good people.

Bump. I may just punt my chance if I can’t figure quant out. Other topics are not nearly as convoluted.

Seriously: instead of bumping this thread, start a new thread with one question, or a set of threads with one question each. You will get a better response.