When comparing two independent groups, psychology researchers commonly use Student’s 't'-tests. Assumptions of normality and homogeneity of variance underlie this test. More often than not, when these conditions are not met, Student’s 't'-test can be severely biased and lead to invalid statistical inferences. Moreover, we argue that the assumption of equal variances will seldom hold in psychological research, and choosing between Student’s 't'-test and Welch’s 't'-test based on the outcomes of a test of the equality of variances often fails to provide an appropriate answer. We show that the Welch’s 't'-test provides a better control of Type 1 error rates when the assumption of homogeneity of variance is not met, and it loses little robustness compared to Student’s 't'-test when the assumptions are met. We argue that Welch’s 't'-test should be used as a default strategy.