In a dependent-samples $t$-test, the initial analysis step involves reducing the two paired scores recorded for each participant into a single value known as a difference score. This is achieved by subtracting one score from the other. It does not matter whether the first set of scores is subtracted from the second or vice versa, provided the order of subtraction is applied consistently across all participants. Often, researchers choose the direction of subtraction so that positive or negative difference scores intuitively align with the expected outcome (e.g., subtracting pretest scores from posttest scores so that a positive difference indicates an increase). Once these difference scores are calculated, the dependent-samples $t$-test functions exactly as a one-sample $t$-test performed directly on these new values.