Gender Differences in Performance on Variables Related to Achievement in Graduate-Level Educational Statistics

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Abstract
To assess gender differences in performance in three graduate level courses in educational statistics, responses from students to a question concerning gender, mathematics pre- and posttests, cloze pre- and posttests, and final exams in statistics were analyzed. Males performed slightly better on the mathematics pretest. When gender and mathematics and cloze pretests were used in multiple regression analyses to predict final examination performance, gender was not a significant predictor for any course. However, the interaction between gender and cloze pretest performance was significant for the Ph.D. level course on multiple regression. Mathematics pretest performance was the primary predictor for performance in the Master's level statistics course; both cloze test and mathematics test performance influenced scores on posttest measure in the Ph.D. level courses. Apparently the influence of entering mathematics ability, comprehension of statistical terminology, and gender varies by the primary emphasis of the course taken. While mathematical ability is most important in basic statistics, it is less important in higher level courses in which an adequate mathematics background is assumed by instructors. In consequence, the importance of comprehension of concepts increases from the Master's level to the advanced Ph.D. level in the educational statistics courses analyzed in this study.

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