# Employee Burnout and Vacation Length Relationship

## Adopting a One-Sample T-Test Approach to an HR Issue: A Scenario Analysis

What factors should the vice-president consider in determining the presence of employee burnout?

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In order to determine the workplace burnout rate among the staff members and identify whether a 1.4-week rest is enough for the staff to recover from months of exhaustive work and be able to deliver the performance of the required quality, one will have to conduct an experiment, in which the variables such as average time that the staff members spend on vacation on an annual basis, the number of employees working for the organization, and the performance rates of the employees. Thus, a comprehensive evaluation of the effects of short vacations on the company members’ performance can be carried out (Schumaker & Tomek, 2013).

Do employees take more than 1.4 weeks of vacation?

According to the conditions provided in the scenario, the p-value can be deemed as rather small. Indeed, being equal to 0.0084, the p-value can hardly be viewed as significant. In other words, the chances of retrieving the results that support the null hypothesis after a random sampling are rather low. Hence, it can be assumed that the difference in the vacation effects rates is strikingly different among the target population. Consequently, it will be reasonable to assume that a significant amount of the staff members suffers from the lack of rest (i.e., takes 1.4 weeks of vacation or less), whereas the other part of the people working in the company seem to be quite satisfied with the opportunities of vacation that they have been provided with and rests for at least 1.4 weeks.

The null hypothesis of the research in question can be defined as the fact that the staff has no problems whatsoever concerning their performance rates regardless of the number of days that they spend on their vacation. Therefore, the p-value, being lower than expected, proves the hypothesis entirely wrong.

What reasons should the vice-president provide to the president to justify the recommendation on employee burnout?

As it has been stressed above, these are the extremely low rates of the p-value and a comparatively high rate of the t-value that make the argument regarding the connection between the burnout rates and the aforementioned 1.4-week vacation so credible (Chase, 2013). Therefore, when presenting the data in question to the company leader and managers, one must put a strong emphasis on the issues in question and, therefore, make it clear that the unreasonably low rates of the p-value prove the lack of homogeneity in the distribution. In other words, while some of the staff members deliver quite bearable results after having less than a 1.4-week vacation, a significant number of other staff members display a complete lack of enthusiasm and extremely low productivity rates due to the lack of sleep and rest.

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Based on the data, is the presence of employee burnout an issue that may negatively impact the company?

It is quite clear that a great number of staff members in the company in question suffer from workplace burnout or, at the very least, are under a consistent threat of experiencing a workplace burnout and, therefore, requiring a reconsideration of the company’s standards for the vacation time for their staff members. The data provided in the course of the analysis indicates that there is a rather obvious problem with the workplace burnout rates in the organization and that it needs to be addressed in a manner as efficient and expeditious as possible. It is, therefore, strongly recommended that the company managers should consider providing the staff with opportunities for longer vacations so that the company members could get enough rest to deliver the appropriate performance rates and contribute to the organization’s progress.

## Reference List

Chase, C. (2013). Demand-driven forecasting: A structured approach to forecasting. New York City, New York: John Wiley & Sons.

Schumaker, P., & Tomek, S. (2013). Understanding statistics using R. Berlin: Springer Science & Business Media.

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