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hypothesis testing

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    In research, we are testing the null hypothesis and alternative hypothesis. If our alternative hypothesis does not show significant support, do we still benefit from the research? How might our research still be valuable to the researcher? To the field of study?

     

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    When a research project conducts data analysis, often a set of hypotheses is created, establishing the criteria that can be used to answer the project’s research question. Typically, the hypothesis called the alternative hypothesis is central to the analysis and represents a condition that the project has set out to prove. While the alternative hypothesis cannot be proven outright, if the null hypothesis can be rejected, then the alternative hypothesis can be accepted. The null hypothesis is the counterpart of the alternative hypothesis and is stated in language that makes it the logical inverse of alternative hypothesis (McNulty, 2022).

    If the project’s analysis fails to reject the null hypothesis, then the alternative hypothesis cannot be accepted. When this occurs, it is tempting to consider that the research project has been a failure. But, while the project was not able to confirm the alternative hypothesis, and thus answer the research question in a way that implies a successful project, there can still be considerable value in the findings of the project.

    There is always value in the findings of a well-conducted project. Even if project was conducted simply to confirm the results of a prior similar project, there is value in getting unexpected results – even if only to cause the researchers to question the earlier results. Research is not conducted for the purpose of confirming expected results, but to methodically examine a question and bring additional light to a subject. Unexpected results can reveal that earlier results may have some limitations and the previously established truths may be subject to conditions that may not yet be evident.

    In other cases, a research project may provide similar value regardless of whether the alternative hypothesis is accepted. The portfolio project I chose for this course is a good example of this. In the project I chose the research question deals with determining whether a newly implemented medical billing system has the operational capacity to support the organization’s three-year growth plan.  If the project findings show that the forecasted system utilization for the next three years exceeds the system’s capacity, then the alternative hypothesis will be accepted.  In this case, the organization will have gained the understanding that additional systems infrastructure must be deployed to handle the planned growth.  But if the null hypothesis cannot be rejected and the alternative hypothesis cannot be accepted, then the organization will know that the billing system already has the capacity to handle the planned growth. This information will allow the organization to forego the expenditure of time and money necessary to upgrade the system.

    In the case of my portfolio project either outcome has high value. If the alternative hypothesis is accepted, the organization gains the knowledge that the billing system must be strengthened to support the planned growth and system disruptions due to exceeding the systems capacity can be avoided. But if the alternative hypothesis cannot be accepted, then the organization gains the knowledge that it can safely forgo costly system upgrades since the billing system will have the capacity to handle the planned growth.

    References

    McNulty, R., (2022, September 19) A Logical Analysis of Null Hypothesis Significance Testing using Popular Terminology. BMC Medical Research Methodology 22 (1). https://doi.org/10.1186/s12874-022-01696-5

     

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