ebookskerop.blogg.se - Two sample t hypothesis test calculator t test

If so, you can reject the null hypothesis and conclude that the two groups are in fact different. You can compare your calculated t-value against the values in a critical value chart to determine whether your t-value is greater than what would be expected by chance. In this formula, t is the t-value, x 1 and x 2 are the means of the two groups being compared, s 2 is the pooled standard error of the two groups, and n 1 and n 2 are the number of observations in each of the groups.Ī larger t-value shows that the difference between group means is greater than the pooled standard error, indicating a more significant difference between the groups. The formula for the two-sample t-test (a.k.a. You can calculate it manually using a formula, or use statistical analysis software. The t-test estimates the true difference between two group means using the ratio of the difference in group means over the pooled standard error of both groups.

If you want to know whether one population mean is greater than or less than the other, perform a one-tailed t-test.

If you only care whether the two populations are different from one another, perform a two-tailed t-test.

comparing the acidity of a liquid to a neutral pH of 7), perform a one-sample t-test. If there is one group being compared against a standard value (e.g.two different species, or people from two separate cities), perform a two-sample t-test (a.k.a. If the groups come from two different populations (e.g.measuring before and after an experimental treatment), perform a paired t-test. If the groups come from a single population (e.g.One-sample, two-sample, or paired t-test? When choosing a t-test, you will need to consider two things: whether the groups being compared come from a single population or two different populations, and whether you want to test the difference in a specific direction.

If your data do not fit these assumptions, you can try a nonparametric alternative to the t-test, such as the Wilcoxon Signed-Rank test for data with unequal variances.

have a similar amount of variance within each group being compared (a.k.a.

are (approximately) normally distributed.

The t-test is a parametric test of difference, meaning that it makes the same assumptions about your data as other parametric tests. If you want to compare more than two groups, or if you want to do multiple pairwise comparisons, use an ANOVA test or a post-hoc test.

Frequently asked questions about t-testsĪ t-test can only be used when comparing the means of two groups (a.k.a.