A Model of Statistics Achievement Using Spatial Ability, Feminist Attitudes and Mathematics-Related Variables as Predictors

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Abstract
Subjects for this study were graduate students enrolled in inferential statistics classes at a midwestern university. The study was conducted to determine the importance of spatial ability, attitudes toward mathematics, mathematical background, masculinity-femininity of interest pattern, attitudes toward feminist issues, student sex, and verbal and mathematical ability as predictors of achievement in applied statistics courses for male and female students. Regression analyses were performed comparing full versus restricted models. The amount of variance in statistics achievement accounted for in the full model which included all the previously mentioned sets of predictor variables was .60. The most important predictor variable set was attitudes toward feminist issues (reduction in R2 = .1861). Sex-related differences were found on all variable sets except verbal and mathematical ability.