Some Determinants of Student Performance in Introductory Statistics

• Activity Number: 247
• Type: Contributed
• Date/Time: Monday, August 2, 2010 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistical Education
• Author(s): Jenting Wang*+ and Shuyi Tu
• Companies: State University of New York at Oneonta and University of Michigan, Flint
• Keywords: Introductory Statistics ; Correlation ; Principal Component Analysis ; Multiple Linear Regression

Abstract

Introductory Statistics is a course required for most of the college students. In a previous study, a model including explanatory variables such as students' overall and math grades in high school and in college, SAT scores, number of collegiate and math credits earned was established to determine the significant variables in predicting students' grades this course. This study aims to further identify other variables for succeeding the course, such as student's major, attendances, the amount of time and efforts students put on for the course and other courses outside the classroom, or the weekly hours students work as a job. Survey questionnaires from students taking the course were collected for the study. Predictions on student's grade may be achieved by the method of principal component analysis.