Prediction of Learning Achievement on Business Statistics Course of the Accounting Students at the University of the Thai Chamber of Commerce Using Discriminant Analysis

Abstract

This research aims at predicting learning achievements on business statistics course using discriminant analysis and based on non-intellectual variables to classify students into two groups: low-achievement and high-achievement students. 269 accounting students at the University of the Thai Chamber of Commerce were chosen as the subjects of this study. All of the students took the business statistics course in the first semester of the academic year 2016. The questionnaire was used to elicit the data, and it comprises five parts as follows: a) bio-social data and general information of the students; b) attitudes of the students towards learning and contents; c) teaching behaviors; d) learning behaviors of the students; and e) personal behaviors of the students. Results include that attitudes of the students towards the business statistics subject _(X2) and towards the subject content _(X3) can discriminate students of low and high requirementgroups at the accuracy rate of 60.6 percent. The derived discriminant equation in raw scores is:Y = - 2.841 + 3.202 X2– 2.195 X3. The results indicate that instructors should try to find a way toimprove the attitude of the students towards business statistics and show how to apply statistics to solve real-world problems to increase learning achievements of the students.