The so-called "exact" conditional tests are very popular for testing hypotheses in the presence of nuisance parameters. However, in the context of discrete distributions, they must be supplemented with randomization to become exactly of size a, the nominal significance level. This practice is undesirable since irrelevant events should not affect one's decision. Consequently, the conditional test without randomization, while still called "exact," becomes conservative. As an unconditional alternative, a methodology is developed to compute the exact size of any test when the null power function is of a given form. This approach is a way of catering to the worst possible configuration of the nuisance parameter by maximizing the null power function over the domain of the nuisance parameter. As special cases, the * attained power 1-3. Therefore, Table A. 5 is sufficient for