# Hypothesis Testing: Intrinsic & Extrinsic Job satisfaction

See attached data set file.

Using AIU's survey responses from the AIU data set, 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.

The report should be well written and should flow well with no grammatical errors. It should include proper citation in APA formatting in both the in-text and reference pages and include a title page, be double-spaced and in Times New Roman, 12-point font. APA formatting is necessary to ensure academic honesty.

Be sure to provide references in APA format for any resource you may use.

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.

https://brainmass.com/statistics/students-t-test/hypothesis-testing-intrinsic-extrinsic-job-satisfaction-300093

#### Solution Summary

The solution provides step by step method for the calculation of test statistic for the comparison of population mean. The solution also provides information on when to use a t-test and when to use a z-test and why samples are used instead of populations. Formula for the calculation and Interpretations of the results are also included. Interactive excel sheet is included. The user can edit the inputs and obtain the complete results for a new set of data.