To calculate a t-Test online just select one metric Variable and one nominal Variable with two values. Here you can easily calculate a t-test online, just copy your data into the upper table and select one or two variables.
- One sample t-test Calculator: If you click on a metric variable and specify the test value, a one sample t test is calculated
- Independent t-test Calculator: If you click on one metric variable and one nominal variable with two categories, an independent samples t test is calculated
- Paired t-test Calculator: If you click on two metric variables, a paired samples t test is calculated.
One sample, independent samples, paired samples
There are different types of t-tests, each with its own specific purpose. The main differences between these t-tests lie in the nature of the data being compared (independent or paired) and the purpose of the test (comparing two groups, comparing paired observations, or comparing a sample mean to a known value).
Here are the three most common types of difference t-tests:
Independent samples t-test
This test is used to compare the means of two independent groups. It assumes that the two groups are independent of each other, and the observations within each group are normally distributed. The independent samples t-test is appropriate when you want to determine if there is a significant difference between the means of two distinct groups. If you have more than two groups you can calculate an analysis of variance online.
Paired samples t-test
This test is used when you have paired or matched observations in two groups. It compares the mean differences between the paired observations. The paired samples t-test assumes that the differences between paired observations are normally distributed. It is commonly used when you want to evaluate if there is a significant difference before and after an intervention or when comparing related observations within the same subjects. If you have more than two paired groups you can use the Repeated measures ANOVA Calculator
This test compares the mean of a single sample to a known or hypothesized value. It is used when you have a sample and want to determine if the mean of that sample significantly differs from a specified value. The one-sample t-test assumes that the observations are normally distributed.
It is crucial to choose the appropriate t-test based on the specific research question and the characteristics of the data.
Assumptions for the t-test
To calculate a t-test, the individual groups must be normally distributed. If the assumptions are not met, a non-parametric test can be used. For example, you can calculate the Mann-Whitney U test online or in the paired case use the Wilcoxon Signed-Rank test calculator.