A hypothesis test study that would assist me in my work, in some way, includes testing the impact of chamomile tea on an individual's level of anxiety. I would begin my study by defining the null statement, which is typically the accepted fact (Edge, 2019) . The null hypothesis is that chamomile tea has no impact on an individual’s level of anxiety. The alternative statement, the opposite of the null statement, would be that chamomile tea can reduce the individual’s level of anxiety. The next step would involve identifying the significant level, which is the probability of disregarding the null statement when it is true. I would set the significance level at 0.20 to ensure that I have a better shot at proving the alternative hypothesis. I would then conduct the test by providing one group with chamomile tea and the other with a placebo. I would then measure the self-reported levels of anxiety of the individuals in both groups. I would then calculate the p-value, which depicts the probability of receiving an effect more extreme as the one in my sample data, assuming the null statement is true (Hanneman et al., 2013) . I would then compare my calculated p-value with the significance level to determine whether the null hypothesis should be accepted or rejected. If the p-value is below the established significance level, the null hypothesis will be disregarded.
The variable to be tested is the individual's level of anxiety, given that it is the dependent variable. It can be measured through the Hospital Anxiety and Depression Scale. My guess of the value of the variable would be 5 for an individual with a low level of anxiety.
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If the results show that the p-value is lower than the established significance level, the null hypothesis will be disregarded, and, in effect, I would seek chamomile tea to reduce my level of anxiety.
References
Edge, D. (2019). Statistical thinking from scratch: A primer for scientists . Oxford, United Kingdom: Oxford University Press.
Hanneman, R., Kposowa, A. J., & Riddle, M. (2013). Basic statistics for social research . San Francisco, CA: Jossey-Bass, a Wiley imprint.
