Paired T-Test Calculator

Dependent T test
Video Information T equal σ calculator T unequal σ calculator

Test calculation

If you enter raw data, the tool will run the Shapiro-Wilk normality test and calculate outliers, as part of the paired-t test calculation.

Enter raw data directly
Enter raw data from excel
Enter summarized data

Enter sample data

Header: You may change groups' name to the real names.
Data: When entering data, press Enter after each value.
The number of observations must be identical in both groups. (Difference = right - left)

The tool ignores empty cells or non-numeric cells.

Enter sample data

You may copy data from Excel, Google sheets or any tool that separate data with Tab and Line Feed.
Copy the data, one block of 3 consecutive columns includes the header, and paste below.
Copy the data,
example from excel

It is okay to leave empty cells, empty cells or non numeric cells won't be counted


count: outliers ,based on the Tukey's fences method, k=1.5
validation message


H0: μd = μ0
H1: μd < > μ0
Test statistic
Chi2 statistic
T-student distribution
t distribution left tailed t distribution two tailed t distribution right tailed

R Code

The following R code should produce the same results:

Target: the test compares the means of the same items in two different conditions or any others connection between the two samples when there is a one to one connection between the samples. The test uses the t distribution. more

Two-tailed test example:
Treatment is given to 50 people to reduce the cholesterol level. The expected reduction is 10mg/dL. The researcher takes two measures for each person before and after the treatment. The average reduction of the cholesterol level is 12mg/dL. (xd= 12mg/dL n=50). The standard deviation of the reduction is 2.2mg/dL. Sd=2.2mg/dL μ0=10mg/dL In this case, the researcher would like to know if μ0 is correct.
Both results are interesting, if the reduction is larger than the expected or if it is lower.

Right-tailed example.
Does the treatment for pattern hair loss effective?
Measurment: hair density, hairs per square cm.
Check the same person before and after 6 months treatment.

H0: the base assumption - identical results before and after the treatment.
H1: the opposite of base assumption - after treatment gets a larger density.