A one-tailed hypothesis test is used when the research hypothesis predicts a direction of the effect (greater than or less than a certain value) can be categorized as a right-tailed test or a left-tailed test. Right-tailed test: This test is used when it is hypothesized that the population parameter is greater than a specific value. Using an example from my work experience, this could be if we expect that a new medication will lead to an improvement in patient outcomes, we would test if the mean outcome for patients receiving the new medication is greater than a standard baseline. Left-tailed test: This test is used when we hypothesize that the population parameter is less than a specific value. Using an example from my work experience, if we expect a reduction in infection rates due to a new hygiene protocol, we would use a left-tailed test to determine if the infection rate is significantly lower than our historical average. A two-tailed hypothesis test is used when the research hypothesis does not predict a specific direction of the effect, but there will be a difference, either greater or smaller than the specified value. In my experience, we might test if there is any difference in the average weight of residents before and after implementing a new nutrition program, without hypothesizing whether the weight average will increase or decrease