Imagine that we have a before and after reading for each item in the sample: for example we might have measured blood pressure before and after administration of a new drug. We can't pool the results and compare the means before and after the change, because each patient will have a different baseline reading. Instead we calculate the difference between before and after measurements in each patient, and calculate the mean and standard deviation of the differences. To test whether a significant change has taken place, we can then test the null-hypothesis that the true mean is zero using the same procedure we used in the single sample cases previously discussed.
That means we can: