This report discusses how factors such as sex, major, mathematics background, and dominant learning style can affect student performance in statistics. It is almost unarguable that the introductory statistics course is the most widely feared course on most university campuses. Dropout and failure rates are extremely high. Students come into the course with low expectation of success., and I have often wondered and talked with colleagues about this fear and lack of success. Can we identify any factors that affect our students' performance in the "Introduction to Statistics" course? Can we determine "what makes a student's statistical clock tick?" Or perhaps more precisely, "what prevents a student's statistical clock from ticking?" Do factors such as sex, major [field of study], class [freshman (first year), sophomore (second year), junior (third year), senior (fourth year)] or mathematics background have a bearing on student performance? For the above factors, no big surprise were found. But another factor, suggested to me by a colleague in the Psychology Department produced a rather stunning result. That factor is the student's dominant learning style.
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The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education