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Job Satisfaction Survey - Determination of Sample Size

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1. Need to provide an overview of the contents of the Research Paper and apply the concepts to the Job Satisfaction Survey attached.

2. Cover the concept of the techniques used to estimate sample size.

3. Determine the required sample size for estimating a single population mean.

4. Conclusion

[Please refer to the attachment for details].

Determination of Sample size for a Relative Quality Improvement.

Full Text Available By: McGrath, Richard N.; Qixuan Chen. Quality Engineering, Jul2008, Vol. 20 Issue 3, p309-320, 12p, 4 charts, 2 graphs, 1 bw; DOI: 10.1080/08982110802035453; (AN 32746637)

Database: Business Source Premier.

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https://brainmass.com/statistics/sample-size-determination/job-satisfaction-survey-determination-sample-size-299933

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The solution provides a detailed overview of the contents of the given research paper based on determination of Sample Size for relative quality improvement and the application of the methods and concepts disscussed in the paper on the Job Satisfaction Survey.

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See Also This Related BrainMass Solution

Two-tailed hypothesis test on a job satisfaction survey

See attached data set files.

Using AIU's survey responses from the AIU data set attached below, complete the following requirements in the form of a report:

Perform a two-tailed hypothesis test on both the intrinsic and the extrinsic variable's data, using a .05 significance level. Begin by creating a null and an alternate statement. Use Microsoft Excel to process your data. Copy and paste the results of the output to your report in Microsoft Word. Identify the significance level, the test statistic and the critical value. State whether you are rejecting or failing to reject the null hypothesis statement.

In a separate paragraph, provide some information on when to use a t-test and when to use a z-test and why. Also, provide some information about why samples are used instead of populations.

Objective:

- Compute mean, median, mode for a set of data.

- Formulate null and alternative hypotheses for applications involving a single population mean, proportion, or variance.

- Use effective communication techniques.

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