![]() ![]() From a t-distribution table, the critical value is 1.734.įor a two-tailed test, you need to find the critical value for both tails. The critical value is the minimum value of the test statistic that will lead to the rejection of the null hypothesis.įor example, suppose you are conducting a one-tailed test with a level of significance α = 0.05 and degrees of freedom df = 19. Once you know the type of test, level of significance, and degrees of freedom, you can find the critical value from a statistical table. The formula for degrees of freedom depends on the type of test and the sample size.įor a one-tailed test with a sample size of n, df = n - 1.įor example, if you have a sample size of n = 20, the degrees of freedom for a one-tailed test would be df = 20 - 1 = 19.įor a two-tailed test with a sample size of n, df = n - 2.įor example, if you have a sample size of n = 30, the degrees of freedom for a two-tailed test would be df = 30 - 2 = 28. ![]() The degrees of freedom, denoted by df, represent the number of independent pieces of information in the sample that can vary. Common levels of significance are 0.05 (5%) and 0.01 (1%), but the specific value depends on the researcher's preference and the context of the study. The level of significance, denoted by α (alpha), is the probability of rejecting the null hypothesis when it is true. In a two-tailed test, the null hypothesis is that there is no effect, without specifying the direction of the effect. In a one-tailed test, the null hypothesis is that there is no effect or a specific direction of effect (i.e., "greater than" or "less than"). The first step is to determine whether you are conducting a one-tailed or two-tailed hypothesis test. Step 1: Determine the Type of Hypothesis Test ![]()
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