A problem that often surfaces in the use of the "t"-test is the absence of critical values for common sample sizes. This problem may cause "guilt" on the part of the professor who must advise students when they encounter discrepancies between their own calculations of the degree of freedom and critical values provided in popular statistics and research textbooks. To avoid hazards of interpolating, professors often suggest using a higher or lower critical value, which usually differs only in the thousandths place. The current study is a Monte Carlo investigation comparing the robustness and power properties of the independent means "t"-test when using the correct critical value versus the approximate values under normal and various non-normal distributions at different alpha levels. The results indicate that the lower critical value allows increased chances of making a Type I error. In the worst case, use of the higher critical value resulted in a modest (6.25%) loss in power. Two data tables are provided. (TJH)