Directional and non-directional hypotheses can be easily interchanged according to the hypothesis the researcher is testing. For instance, a drug company might predict that a drug will help a subject lose weight while another drug company might predict that a drug will alter a subject's weight.
Describe a situation in which you would test a directional hypothesis. Be sure to state the independent variables (e.g., drug or placebo) and the dependent variables (e.g., weight loss) clearly and explain why the hypothesis is directional. Then, revise the same situation to make it non-directional. Explain which according to you is more appropriate and why. Evaluate the practice of altering the alpha level so that a two-tailed test will have a 5% rejection region on both sides of the curve for a total of 10% instead of having a 2.5% rejection region on both sides in order to maintain a 5% alpha.
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Situation with Directional Hypothesis:
Let's consider a situation in which a drug company is testing a new weight loss drug. The independent variable in this case would be the drug itself, which will be administered to a group of participants. The dependent variable would be weight loss, measured as the change in participants' body weight over a specific period of time.
In this scenario, the directional hypothesis would be that the drug will lead to weight loss in the subjects. The prediction is specific and states the expected direction of the effect, suggesting that the drug will decrease participants' weight.
Revised situation with Non-Directional Hypothesis:
To make the situation non-directional, we would revise the hypothesis to state that the drug will have an effect on altering participants' weight, without specifying the direction of the effect. The new hypothesis would be that the drug will cause a change in weight, giving equal consideration to the possibility of weight loss or weight gain.
Appropriateness of Directional vs. Non-Directional Hypotheses:
The choice between a directional and non-directional hypothesis depends on the specific research question and the available evidence. A directional hypothesis is appropriate when there is already substantial evidence or theoretical basis to support a specific direction of the effect. For instance, in the case of a weight loss drug, if previous studies have consistently shown that similar drugs have caused weight loss, a directional hypothesis predicting weight loss would be reasonable.
On the other hand, a non-directional hypothesis is more appropriate when there is limited or conflicting evidence regarding the expected direction of the effect, or when the research question is exploratory in nature and aims to investigate any potential effect, positive or negative.
Practice of Altering Alpha Level in Two-Tailed Tests:
The alpha level determines the threshold for statistical significance, indicating how unlikely an observed result would be due to chance. By convention, a 5% alpha level is commonly used to determine statistical significance in hypothesis testing. This corresponds to a 2.5% rejection region on each side of the distribution curve in a two-tailed test.
Altering the alpha level to have a 10% rejection region (5% on each side) in a two-tailed test would increase the likelihood of rejecting the null hypothesis. While it may seem advantageous to have a higher chance of detecting an effect, altering the alpha level in this manner can lead to an increased risk of committing a Type I error (false positive).
Maintaining a 5% alpha level is generally recommended as it strikes a balance between being sensitive enough to detect meaningful effects while controlling the risk of Type I errors. The conventional alpha level has been widely used and is backed by statistical theory and practice. It is important to adhere to established standards to ensure the reliability and validity of statistical inferences.