T-Test Calculator
Run a one-sample or two-sample Student's t-test from raw data. Get the t statistic, degrees of freedom, two- and one-tailed p-values, and significance at p = 0.05 and p = 0.01.
Pick a test
Need at least 2 values.
t statistic
0.7276
df = 9
Not significant at p = 0.05
P-value (two-tailed)
0.485351
P-value (one-tailed)
0.242676
Mean 1
5.05
Std. dev. 1
0.2173
n1
10
Hypothesized mean
5
Frequently Asked Questions about the T-Test Calculator
What is the null hypothesis in a t-test?
The default claim that there is no real difference: the population mean equals your hypothesized value (one-sample), or the two population means are equal (two-sample). The p-value tells you how surprising your data would be if that claim were true.
What does the p-value mean?
The probability of seeing a t statistic at least as extreme as yours if the null hypothesis is true. A small p-value (commonly below 0.05) is evidence against the null. It is not the probability that the null is true.
When do I use one-tailed vs two-tailed?
Two-tailed tests for any difference and is the safe default. Use one-tailed only when your hypothesis is directional before seeing the data, for example you predicted the new method would be faster, not just different.
Equal variance or unequal variance (Welch)?
Welch's t (unequal variance) is the modern default. It handles different sample sizes and different spreads without bias. Use pooled (equal-variance Student's t) only when you have strong reason to believe the population variances match.
Should I use a t-test or a z-test?
Use a t-test when you estimate the standard deviation from the sample, which is almost always. Use a z-test only when the population standard deviation is known. With n above ~30, the two give nearly identical p-values.