5. Discuss the implications of changing the level of significance to a larger value. What mistake or error could increase if the level of significance is increased?

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QUESTION 5.

(Data file included: Yes; In Sheet: Quality):

Quality Associates, Inc., a consulting firm,

advises its clients about sampling and statistical procedures that can be used to control their

manufacturing processes. In one particular application, a client gave Quality Associates a sample of 800 observations taken while that client’s process was operating satisfactorily. The sample standard deviation for these data was 0.21; hence, with so much data, the population standard deviation was assumed to be 0.21. Quality Associates then suggested that random samples of size 30 be taken periodically to monitor the process on an ongoing basis. By analysing the new samples, the client could 5 quickly learn whether the process was operating satisfactorily. When the process was not operating satisfactorily, corrective action could be taken to eliminate the problem. The design specification indicated that the mean for the process should be 12. Corrective actions should be taken is the mean of the process does not equal to 12.

4. Compute limits for the sample mean ? ̅around μ = 12 such that, as long as a new sample mean is within those limits, the process will be considered to be operating satisfactorily. Use α = 0.05. If ? ̅ exceeds the upper limit or if ? ̅ is below the lower limit, corrective action will be taken. These limits are referred to as upper and lower control limits for quality-control purposes.

5. Discuss the implications of changing the level of significance to a larger value. What mistake or error could increase if the level of significance is increased?

6. Quality Associates now believes that if the mean of the process from the sample exceeds 12, then they won’t as alarmed if it was to go below 12. Conduct a hypothesis test under this scenario for each sample at the 0.05 level of significance and determine what corrective action, if any, should be taken in case the sample results in mean values less than the expected. Provide the test statistic and p value for each test.

 
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