What is the procedure involved in performing hypothesis tests?
When testing a hypothesis, researchers must follow defined procedures. There are different hypothesis tests that researchers can perform. All these tests, nevertheless, involve five procedures. The first step in hypothesis testing entails defining the null hypothesis, the alternative hypothesis and selecting the significance level (Anderson et al., 2020, p.389). While there are only three potential combinations of the two hypotheses, this procedure can be challenging. The null hypothesis should always include an equality sign irrespective of whether the researcher obtains the argument indirectly or directly from the issue being examined (Anderson et al., 2020, p.391). Researchers usually select all the three before data observation.
The second procedure entails the researcher selecting and computing the required test statistic. Investigators regard the null hypothesis to be true unless it is proven otherwise through empirical data (Anderson et al., 2020, p.404). Additionally, the test statistic should be selected based on the parameter being measured and it must be as general as possible to ensure convenience. The test statistic should also rely on a statistic that assesses the required parameter and be useful irrespective of the parameter value. The third procedure during hypothesis testing focuses on finding the value of the decision rule. Regarding the inference on the significance level and in the presence of the properties of the significance level estimator, it is expected that the average of the sample will be near the true mean of the population irrespective of whether or not the significance levels are values formed in the null hypothesis (Anderson et al., 2020, p.624). Investigators use the decision rule to decide whether or not to reject the null hypothesis.
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The fourth procedure entails deciding the null hypothesis by determining the decision rule threshold based on the significance level (Anderson et al., 2020, p.421). The final procedure involves the statistical conclusion where investigators interpret the choice of whether or not to reject the null hypothesis in the context of the issue under exploration.
Reference
Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2020). Statistics for Business and Economics. Cengage Learning.
