Six Steps of Testing Hypothesis
Hypothesis testing is a statistical method used to analyze and test assumptions concerning a specific population parameter. Hypothesis testing allows the analyst to compare the result with the null hypothesis. It is only rejected when the probability is below the predetermined level of significance. There are six essential steps that analysts use to test the hypothesis. The first step is setting the hypothesis by defining the research, null and alternate hypotheses (Yin, 2017). The research hypothesis is the assumption that is considered true for the investigation. The research hypothesis outlines a statement that will guide the entire research. The alternate hypothesis is the position that states something happens but offers a new theory instead of the null hypothesis. Thus, the researcher is required to differentiate between the general research hypotheses and the null hypothesis.
The second step is developing assumptions that will guide the hypothesis testing. Different factors are considered when developing hypothesis testing assumptions. These include’ the data measurement level, the testing significance level, characteristics of the sample when applying the statistics testing, sampling method and sample size, data distribution and population characteristics knowledge. This information provides ideal background that allows the researcher to set the right parameter for analyzing and testing the hypothesis.
The third step is defining the test statistics that will be used during the process. The research must elaborate the confidence interval structure by highlighting the notations and equations used to test levels of significance. The fourth step involves highlighting the probability statement and outlining the region of rejection. Before starting calculations, the researcher must highlight the test used to reject or fail to reject the null hypothesis(Flores-Ruiz et al., 2017). The definition of rejection areas allows them to determine critical values when deciding.
The fifth step is calculating the based on the sample provided using the highlighted statistical methods. The researcher must ensure all the calculation parameters have been considered and adhered to during the discussion. The testing of the statistic measure requires the integration of all notation and equations. The last process highlights the conclusion by indicating the acceptance or rejection of the null hypothesis and the statement of result. The last step also allows the researchers to highlight or recommend future research progress (Simonsohn et al., 2019). Hypothesis testing is used in public health to identify whether new drugs can manage certain disorders. For instance, hypothesis testing has been conducted to determine the viability of different COVID 19 in preventing corona virus.
Reference.
Flores-Ruiz, E., Miranda-Novales, M. G., & Villasís-Keever, M. Á. (2017). The research protocol VI: How to choose the appropriate statistical test. Inferential.
Simonsohn, U., Simmons, J. P., & Nelson, L. D. (2019). Specification curve: Descriptive and inferential statistics on all reasonable specifications. Available at SSRN 2694998.
Yin, R.K., (2017). Case study research and applications: Design and methods. Sage publications