A t-test is a statistical hypothesis test that determines whether there is a statistically significant difference between the means of two groups. It's particularly useful when the sample sizes are small and the population standard deviations are unknown (which is often the case when dealing with experimental or simulation data). The t-test considers both the difference in means and the variability (standard deviation) within each group to calculate a t-statistic. This t-statistic is then used to determine a p-value, which represents the probability of observing the data (or more extreme data) if there were actually no difference between the groups. A small p-value (typically less than a chosen significance level, like 0.05) indicates strong evidence against the null hypothesis (that there is no difference), and thus suggests a statistically significant difference between the means.