To perform a paired (dependent) T-test in GraphPad Prism you will need to enter two groups of data into separate columns. Upon opening GraphPad Prism, select the ‘**Column**’ type for the ‘**New Table & Graph**’ option. Then select ‘**Enter paired or repeated measures data – each subject on a separate row**’ as the ‘**Enter/import data**’ choice.

Alternatively, you can go to ‘**File > New > New Data Table & Graph …**’.

For this tutorial, I will use an example of comparing the number of viable cells before and after a 6-hour treatment with drug X. The data is entered into two columns labelled ‘before’ and ‘after’.

**“There is no difference in the number of viable cells before and after a 6-hour treatments with drug X”.**

And our alternative hypothesis will be:

**“There is a difference in the number of viable cells before and after a 6-hour treatments with drug X”.**

## Performing the paired T-test

To perform a paired t-test, first go to ‘**Insert > New Analysis …**’.

This will open a new window. Here you need to tell GraphPad which test to perform. Select the ‘**t tests (and nonparametric tests)**’ analysis and make sure the two datasets are ticked on the right window.

The next window will ask you to specify whether the T-test is an unpaired (independent) or paired (dependent) test. In this case, select the ‘**paired**’ option.

Also, select whether the test will be a parametric or nonparametric test. Under ‘**Assume Gaussian distribution**’, select ‘**Yes. Use parametric test**’. This will ensure a paired T-test is performed.

The final option titled ‘**Choose test**’ refers to whether your two datasets have equal variance. Select, ‘**Paired t test (difference between paired values are consistent).**’

If you want to change any other settings, such as the confidence level, go to the ‘**Options**’ tab. For our purpose we are going to leave everything in the default settings, but will select ‘**Descriptive statistics for each data set**’ which will produce the mean and standard deviation for each group.

Click ‘**OK**’ to perform the test.

## Output

The great thing about GraphPad Prism for statistical testing is that the output is very user friendly and self-explanatory. All you need to do is to refer to the ‘**Paired t test**’ section.

- P value – The exact p value.
- P value summary – A summary of the p value as represented by asterisks. These are useful to signify the level of significance on graphs, for example.
- Significantly different? (P<0.05) – A straight yes or no answer for the paired t test.
- One- or two-tailed P value? – Whether a one- or two-tailed paired t test was performed.
- t, df – The t statistic and the degrees of freedom in the analysis.
- Number of pairs – The number of pairs of data in the analysis.

GraphPad also gives you other descriptive information for each dataset (under the ‘**How big is the difference?**’ section) and an indication for how effective the pairing between the datasets was (under the ‘**How effective was the pairing?**’ section).

## Interpretation

By looking at the ‘**Significantly different? (P<0.05)**’ output, a ‘**Yes**’ is given which essentially means that our results are significantly different from each other. The exact p value is given next to ‘**P value**’. In this case a p value of < 0.0001 indicates a very significant difference, since this is less that our level of significance threshold of 0.05.

So, after performing the paired T-test in GraphPad we now know that there is a significant difference between the number of cells before and after the treatment with drug X for 6-hours. In which case, we reject the null hypothesis and accept the alternative hypothesis.

## Reporting

If we were to report the results of this paired t test in a single sentence, we could write:

“There was a higher number of cells before (10257 ± 1430 cells) than after (5239 ± 861 cells) a 6-hour treatment with drug X, t(6) = 13.55, p < 0.0001.”

This includes the mean and standard deviation (this information can be found in the ‘**Descriptive statistics**’ sheet) for each group, as well as the t statistic, degrees of freedom and the all-important p value.