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![]() ![]() That is because the p-value is actually a probability, and its value, and calculation method, depends on the underlying probability distribution. The p-value that is determined from your results is based on the test statistic, which depends on the type of hypothesis test you are using. Statistically significant p-value results can provide some of that evidence, which makes it important to know how to calculate p-values. 01.Īnother way to consider the null hypothesis that might make the concept clearer is to compare it to the adage “innocent until proven guilty.” It is assumed that the null hypothesis is true unless enough strong evidence can be found to disprove it. 05, although, depending on the circumstances, it could be set at another value, such as. The researcher will typically set that point, which is the probability of rejecting the null hypothesis given that it is true, prior to conducting the trial. However, at some point, you must consider that the new drug may just have a better longevity. In theory, this could still be a random outcome, due to chance, even if the null hypothesis were true. Let’s say your results show that the new drug lasts twice as long as the standard drug. If we assume the null hypothesis is true, how much longer does the new drug have to last? This is where the critical p-value comes in. Next, we need to determine our criterion for deciding whether or not the null hypothesis can be rejected. We are not interested in the area under the lower side of the curve. Because H a includes “greater than,” this is an upper-tailed test. Note that the null hypothesis states that there is no difference in the mean values for the two drugs. H a: the mean longevity of the new drug is greater than that of the standard drug H 0: the mean longevity of the new drug is equal to that of the standard drug ![]() ![]() It represents what you’re trying to find evidence to support.īefore we conduct the clinical trial, we create the following hypotheses: The alternative hypothesis (H a) states that a relationship exists or that there is a difference between two groups. The null hypothesis (H 0) is what you’re trying to disprove, usually a statement that there is no relationship between two variables or no difference between two groups. Stating your null and alternative hypotheses is the first step in conducting a hypothesis test. But how can we determine this scientifically? We do this through hypothesis testing. If your results show that the average length of time patients are pain-free is longer for the new drug than that for the standard medicine, how will you know that this is not just a random outcome? If this result falls within the green shaded area of the graph, you may have evidence that your drug has a longer effect. You are planning a clinical trial for your drug. P-values are used in hypothesis testing to find evidence that differences in values or groups exist. From previous research, you know that the underlying probability distribution for both medicines is the normal distribution, which is shown in the figure below. Please note that this is an extremely simplified example, intended only to demonstrate the concepts. P-values are determined through the calculation of the test statistic for the test you are using and are based on the assumed or known probability distribution.įor example, you are researching a new pain medicine that is designed to last longer than the current commonly prescribed drug. ![]() The p-value, or probability value, is the probability that your results occurred randomly given that the null hypothesis is true.
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