We proposed an extended form of the Govindarajulu and Barnett margin of error (MOE) equation and used it with an analysis of variance experimental design to examine the effects of aggregating student evaluations of teaching (SET) ratings on the MOE statistic. The interpretative validity of SET ratings can be questioned when the number of students enrolled in a course is low or when the response rate is low. A possible method of improving interpretative validity is to aggregate SET ratings data from two or more courses taught by the same instructor. Based on non-parametric comparisons of the generated MOE, we found that aggregating course evaluation data from two courses reduced the MOE in most cases. However, significant improvement was only achieved when combining course evaluation data for the same instructor for the same course. Significance did not hold when combining data from different courses. We discuss the implications of our findings and provide recommendations for practice.