Discussion board
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For this engagement exercise, we perform a Goodness-of-fit test using StatdiskLinks to an external site..
Background of the study:
Imagine that you work for an HR department. Your team provides mandatory training to employees who work from home. Your supervisor wants to know the best time of day to hold synchronous Zoom sessions. You decide to ask 100 remote employees their preferred time to meet for a Zoom session (Morning, Afternoon, or Evening). You record the number of observations for each category (Prefer Morning, Prefer Afternoon, Prefer Evening). You want to know: Is there a difference in employee preference for the time of day to train online? To answer this question, you use a Goodness-of-fit test to compare observed preference scores with expected scores.
Note: For this exercise assume that all the preferred times of day will be the same. To access the dataset , click on the following document: M7 Engagement Chi-Square dataset.xlsxDownload M7 Engagement Chi-Square dataset.xlsx
The claim: The time of day matters in terms of employee preferences for online training.
State the null and alternative hypothesis.
To conduct the Analysis:
Use Statdisk software to run the calculations. Click on the following instructional video:Statdisk Goodness of fitLinks to an external site.
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Once in Statdisk, upload your dataset from the Excel doc. Click on Analysis > Goodness of fit> Equal expected frequencies > indicate col 2 in the drop-down box > Evaluate. Also click on Plot to obtain a graph of the x^2 distribution that includes the test statistic and critical value. Include the Printout and graphic in your post.
The Decision and the Conclusion:
We compare the p-value to the significance level to make a “decision. (Explain how you made your decision). Translate that decision back to the null and alternative hypothesis.
Finally, do the Goodness-of-fit test results support the original claim?
Critical Assessment:
Do the test results give you what you need to answer your research question? Put yourself in the shoes of the consultant: In looking back at your research process, what could the limitations be for using this type of statistical test for this research question?
How could you build on this research to learn more about the experience of new employees?
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