What is the T-Test Calculator?

Calculate t-test statistics for one-sample and two-sample hypothesis tests. Enter your data to get the t-statistic, degrees of freedom, p-value, and whether to reject the null hypothesis.

Is the T-Test Calculator free to use?

Yes. The T-Test Calculator is free to use on Calculate.co.nz, with no sign-up, paywall or account required.

Is the T-Test Calculator made for New Zealand?

Yes. It is built for New Zealand and uses current New Zealand rules and rates where they apply. Results are indicative estimates and not financial advice.

T-Test Calculator

This calculator runs the three standard t-tests used to compare two sets of sample data and decide whether the difference between their means is statistically meaningful, the same three tests found in the Excel Data Analysis Toolpak. You enter your figures into the Data 1 and Data 2 boxes, one value per line, and the results update automatically and appear side by side in three tables: Paired Two-Sample for Means, for matched or repeated measurements, which needs equal-sized data sets, Two-Sample Assuming Unequal Variances (Welch's t-test), and Two-Sample Assuming Equal Variances, a pooled-variance test. Each table shows the mean, variance and number of observations for both variables, plus the degrees of freedom, the t Stat, and the one-tail and two-tail p-values and critical t-values, so you can see straightaway whether your result clears the common 0.05 significance level. The paired test also reports the Pearson correlation between the two data sets, and the equal-variances test reports the pooled variance used in its workings. Use the Reset button to clear both boxes and start again. This suits students, researchers and anyone checking survey, experiment or before-and-after results for a genuine difference rather than random variation. As with any statistical test, the result is only as reliable as the data you enter, so check your sample sizes and assumptions before drawing conclusions from the output.

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Data 1

Data 2

t-Test: Paired Two Sample for Means

	Variable 1	Variable 2
Mean
Variance
Observations
Pearson Correlation
Hypothesized Mean Difference	0
Degrees of Freedom
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail

t-Test: Two-Sample Assuming Unequal Variances

	Variable 1	Variable 2
Mean
Variance
Observations
Hypothesized Mean Difference	0
Degrees of Freedom
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail

t-Test: Two-Sample Assuming Equal Variances

	Variable 1	Variable 2
Mean
Variance
Observations
Pooled Variance
Hypothesized Mean Difference	0
Degrees of Freedom
t Stat
P(T<=t) one-tail
t Critical one-tail
P(T<=t) two-tail
t Critical two-tail

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