The probability of committing a Type II error is called the Power of the test or Beta, denoted as β. Type II error: You fail to reject the null hypothesis when it is actually false. The probability of committing a Type I error is equal to the significance level, often called alpha, and denoted as α. Type I error: You reject the null hypothesis when it is actually true. There are two types of decision errors that one can make when doing a hypothesis test: Interpret the results of the hypothesis test in the context of the question being asked. If the p-value is less than the significance level, we reject the null hypothesis. The p-value tells us the strength of evidence in support of a null hypothesis. Using the test statistic or the p-value, determine if you can reject or fail to reject the null hypothesis based on the significance level. Reject or fail to reject the null hypothesis. Often we are analyzing a population mean or proportion and the general formula to find the test statistic is: (sample statistic – population parameter) / (standard deviation of statistic)Ĥ. 1.įind the test statistic and the corresponding p-value. Determine a significance level to use for the hypothesis.ĭecide on a significance level. These two hypotheses need to be mutually exclusive, so if one is true then the other must be false.Ģ. State the null and alternative hypotheses. Hypothesis TestsĪ hypothesis test consists of five steps: The alternative hypothesis, denoted as H 1 or H a, is the hypothesis that the sample data is influenced by some non-random cause.

The null hypothesis, denoted as H 0, is the hypothesis that the sample data occurs purely from chance.

There are two types of statistical hypotheses: To test whether a statistical hypothesis about a population parameter is true, we obtain a random sample from the population and perform a hypothesis test on the sample data. is the population parameter.Ī hypothesis test is a formal statistical test we use to reject or fail to reject a statistical hypothesis.

The assumption about the height is the statistical hypothesis and the true mean height of a male in the U.S. A statistical hypothesis is an assumption about a population parameter.įor example, we may assume that the mean height of a male in the U.S.

Hypothesis test calculator