# PROVIDE TWO DIFFERENT EXAMPLES OF HOW RESEARCH USES HYPOTHESIS TESTING, AND DESCRIBE THE CRITERIA FOR REJECTING THE NULL HYPOTHESIS HLT 362

**PROVIDE TWO DIFFERENT EXAMPLES OF HOW RESEARCH USES HYPOTHESIS TESTING, AND DESCRIBE THE CRITERIA FOR REJECTING THE NULL HYPOTHESIS HLT 362 **

**Topic 3 DQ 1**

Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis. Discuss why this is important in your practice and with patient interactions.

REPLY TO DISCUSSION

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What is a hypothesis?

A hypothesis is a proposed explanation for a phenomenon. For an idea to be a scientific hypothesis, the scientific method requires that one can test it. (Hypothesis, 2021)

The hypothesis is an educated summation of the outcome between independent and dependent variables and the research process that will test the validity by analyzing the data. (Ambrose, 2018) Healthcare is the evolving study on the improvement of the quality of care. Questioning how to improve the quality is the 1st step. The prediction of the outcome between the two variables of dependent and independent is the hypothesis. With the variables identified, data collection is based on the variables. The research data will reflect the correlation but cannot prove causation that indicates a direct correlation between the cause and effect.

The null hypothesis is essentially the “devil’s advocate” position. That is, it assumes that whatever you are trying to prove did not happen (Hypothesis Testing, 2018)

The increased prevalence of cannabidiol oil (CBD) for pain control leads to a hypothesis. There has not been a study to reinforce nor disprove the statement that CBD use decreases pain. The theory of CBD use will reduce pain with regular consumption. The null hypothesis lacks the data for the relationship between the variables, or there is no effect on them. The data will reflect the patients that utilize CBD and have no pain relief. The alternative hypothesis indicates a relationship between the variables stating the decrease in pain by the subject that takes CBD. This data pattern can be interpreted to reject the null hypothesis, and if rejected, the alternative is accepted.

The use of alternative medicines has increased aromatherapy to reduce or prevent nausea in emergency room patients. There is no data to reinforce or disprove the hypothesis that the arbitrary resolves or decreases nausea in ER patients. The null hypothesis lacks subjective data to correlate the relationship between the variables and the direct effect. The data would be objective that using aromatherapy decreased or relieving nausea. An alternative hypothesis will show a connection between the variables reflecting the decrease or relief of sickness in the subject group. What is an idea?

A hypothesis is a proposed explanation for a phenomenon. For an idea to be a scientific hypothesis, the scientific method requires that one can test it. (Hypothesis, 2021)

The hypothesis is an educated summation of the outcome between independent and dependent variables and the research process that will test the validity by analyzing the data. (Ambrose, 2018) Healthcare is the evolving study on the improvement of the quality of care. Questioning how to improve the quality is the 1st step. The prediction of the outcome between the two variables of dependent and independent is the hypothesis. With the variables identified, data collection is based on the variables. The research data will reflect the correlation but cannot prove causation that indicates a direct correlation between the cause and effect.

The null hypothesis is essentially the “devil’s advocate” position. That is, it assumes that whatever you are trying to prove did not happen (Hypothesis Testing, 2018)

The increased prevalence of cannabidiol oil (CBD) for pain control leads to a hypothesis. There has not been a study to reinforce nor disprove the statement that CBD use decreases pain. The theory of CBD use will reduce pain with regular consumption. The null hypothesis lacks the data for the relationship between the variables, or there is no effect on them. The data will reflect the patients that utilize CBD and have no pain relief. The alternative hypothesis indicates a relationship between the variables stating the decrease in pain by the subject that takes CBD. This data pattern can be interpreted to reject the null hypothesis, and if rejected, the alternative is accepted.

The use of alternative medicines has increased aromatherapy to reduce or prevent nausea in emergency room patients. There is no data to reinforce or disprove the hypothesis that the arbitrary resolves or decreases nausea in ER patients. The null hypothesis lacks subjective data to correlate the relationship between the variables and the direct effect. The data would be objective that using aromatherapy decreased or relieving nausea. An alternative hypothesis will show a connection between the variables reflecting the decrease or relief of sickness in the subject group.

References

Ambrose, J. (2018). Applied Statistics for Health Care. Grand Canyon University.

https://doi.org/https://lc.gcumedia.com/hlt362v/applied-statistics-for-health-

care/v1.1/#/chapter/3

Hypothesis. (2021). Wikipedia. Retrieved April 28, 2021, from https://en.wikipedia.org/wiki/Hypothesis

Hypothesis Testing. (2018). Laerd Statistics. Retrieved April 28, 2021, from https://statistics.laerd.com/statistical-guides/hypothesis-testing-3.php

**MR**

Mayle Rodriguez

replied toIrene Igbinosa

Sep 1, 2022, 3:40 AM

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Irene,

I really liked your discussion post about hypothesis testing and its use in the health care field. Any evidence-based practices that are practiced by the health care professionals are derived from the hypothesis testing (Banerjee et al, 2009). As nurses, knowing and understanding the application of each practice and the research behind it can help in providing better care to the patients and this, in turn, can provide better outcomes and results from the treatment provided. An important aspect of understanding hypothesis testing is the null hypothesis and P-value. The null hypothesis is a formal basis for testing statistical relevance and it states that there is no association between the predictor and outcome variables in a population (Banerjee et al, 2009). So, in an experiment, the data that are analyzed to determine the P-value, the probability of acquiring the study results if by chance the null hypothesis becomes true. Hence, if the P-value of the concerned hypothesis is less than a significant value, then the null value can be rejected but if the P-value of the concerned hypothesis is above the significant value, the null value cannot be rejected.

References:

Banerjee. A, Chitnis. U. B, Jadhav. S. L, Bhawalkar. J. S & Chaudhury. S. (2009). Hypothesis testing, type I and type II errors. Industrial psychiatry journal. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996198/