HLT 362V Topic 3 Discussion 1

HLT 362V Topic 3 Discussion 1 Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis. Discuss why this is important in your practice and with patient interactions. Answer When conducting quantitative research, you are attempting to answer a research question or hypothesis that you have set. One method of evaluating this research question is through a process called hypothesis testing, which is sometimes also referred to as significance testing. The first step in hypothesis testing is to set a research hypothesis. In statistics terminology, the people in the study are the sample and the larger group they represent is called the population. For example, a sample of statistics students in a study are representative of a larger population of statistics students, you can use hypothesis testing to understand whether any differences or effects discovered in the study exist in the population. Hypothesis testing is used to establish whether a research hypothesis extends beyond those individuals examined in a single study. Another example could be taking a sample of 200 breast cancer patients to test a new drug that is designed to eradicate this type of cancer. As much as you are interested in helping these specific 200 cancer patients, the real goal is to establish that the drug works in the population for all cancer patients. In order to undertake hypothesis testing, the research hypothesis should be expressed as a null and alternative hypothesis. The null hypothesis and alternative hypothesis are statements regarding the differences or effects that occur in the population. The evidence is tested against the null hypothesis. When considering whether to reject the null hypothesis and accept the alternative hypothesis, consider the direction of the alternative hypothesis statement. The alternative hypothesis tells us two things. First, what predictions did we make about the effect of the independent variable(s) on the dependent variable(s)? Second, what was the predicted direction of this effect (Laerd Statistics, nd)? A two-tailed prediction means a choice is not made over the direction that the effect of the experiment takes. It simply implies that the effect could be negative or positive. A one-tail prediction usually reflects the hope of a researcher rather than any certainty that it will happen. If the statistical analysis shows that the significance level is below the set cut-off