logo
Products
Technologies
Applications
Services
Resources
Selection Guides
About
T-Test Calculator
Statistical t-tests are useful in determining and comparing significant differences between group means and evaluating if those differences are a result of chance. While the one-sample t-test analyzes the mean of one group against the set average (theoretical mean), the two-sample t-test compares means of two different samples for paired or unpaired data. Both methods assume a continuous data that is randomly selected and normally distributed with equal variances. Under the null hypothesis, which states that the means are equal, a t-statistic is calculated that follows a t-distribution with the associated degrees of freedom and a p value is obtained representing the probability that the null hypothesis is true. For t-statistic less than the t-critical at a p value greater than 0.05 (95% confidence interval), the null hypothesis is accepted. A negative t-statistic can be treated as their positive counterpart. A statistical summary of the data comprising of the mean, confidence interval, median, variance, standard deviation, minimum, maximum, and count is provided to quickly communicate the observations in the sample data. Histograms with embedded density plots, box plots, and normality plots are shown to visualize individual and group differences. A normal distribution for a Q-Q plot is observed when all the data points lie on the red line. Normality assumption is further verified with Shapiro Wilk test calculating a W-statistic. Consequently, for unpaired groups, a variance test based on the ratio of the homogeneity of variance between each group is carried out to determine the type of t-test to be performed. For a ratio of variance greater than or equal to 0.05, an equal variance is assumed and a two-sample unpaired t-test is given. On the other hand, when the ratio of variance between samples is less than 0.05, an unequal variance is assumed and a Welch’s t-test (also for unpaired data sets) is executed.
Data Entry
Feedback
Have a question or a feature request about this tool? Feel free to reach out to us and let us know! We're always looking for ways to improve!
References
This online resource may be cited as follows
MLA
"Quest Graph™ T-Test Calculator." AAT Bioquest, Inc., 17 Nov. 2025, https://www.aatbio.com/tools/one-two-sample-independent-paired-student-t-test-calculator.
APA
AAT Bioquest, Inc. (2025, November 17). Quest Graph™ T-Test Calculator. AAT Bioquest. https://www.aatbio.com/tools/one-two-sample-independent-paired-student-t-test-calculator.
BibTeXEndNoteRefMan
This online resource has been cited in 2 publications, including
A machine learning examination of women’s leadership effectiveness in software development processes
Authors: 
Ferreira, S{\^a}mara Ahyeska Alves and Lima, Danielli Ara{\'u}jo
Therapeutic effects of Lucilia sericata larval excretion/secretion products on Leishmania major under in vitro and in vivo conditions
Authors: 
Sherafati, Jila and Dayer, Mohammad Saaid and Ghaffarifar, Fatemeh
Journal: 
Parasites \& Vectors (2022): 1--12

  • Place the experimental data into the box on the right. This can be done by directly copying from Excel or pasting values in comma-separated, tab-separated, or space-separated formats. If data is being entered manually, only place one value per line. The format should be the following:
    Data Set 1: Group 1Data Set 2: Group 2
    X1Y1
    X2Y2
    X3Y3
    X4Y4
    ……
    For a single data set, a corresponding theoretical mean needs to be entered. In the case of two data sets, users should provide the type of data set being tested i.e. paired or unpaired. To add a new data set, press on the ‘+’ tab above the data entry area. Variables can be named by double clicking the tab but is optional.
  • Verify your data is accurate in the table that appears.
  • Press the "Calculate t-test" button to display results.