Table 1 presents the four possible outcomes of any hypothesis test based on (1) whether the null hypothesis was accepted or rejected and (2) whether the null hypothesis was true in reality.Ī Type I error is often represented by the Greek letter alpha (α) and a Type II error by the Greek letter beta (β ).

These two errors are called Type I and Type II, respectively. You can err in the opposite way, too you might fail to reject the null hypothesis when it is, in fact, incorrect. Even if you choose a probability level of 5 percent, that means there is a 5 percent chance, or 1 in 20, that you rejected the null hypothesis when it was, in fact, correct. If the likelihood of obtaining a given test statistic from the population is very small, you reject the null hypothesis and say that you have supported your hunch that the sample you are testing is different from the population.īut you could be wrong. You have been using probability to decide whether a statistical test provides evidence for or against your predictions.

Quiz: Test for Comparing Two Proportions.

Quiz: Test for a Single Population Proportion.

Test for a Single Population Proportion.Quiz: Two-Sample t-test for Comparing Two Means.Two Sample t test for Comparing Two Means.Quiz: Two-Sample z-test for Comparing Two Means.Quiz: Introduction to Univariate Inferential Tests.Two-Sample z-test for Comparing Two Means.Quiz: Point Estimates and Confidence Intervals.Point Estimates and Confidence Intervals.Quiz: Normal Approximation to the Binomial.Quiz: Populations, Samples, Parameters, and Statistics.Populations, Samples, Parameters, and Statistics.Quiz: Introduction to Numerical Measures.

Type ii error