Models of Screening Bachelor of Science in Applied Statistics and Bachelor of Science in Information Technology Freshman Applicants

Abstract

The study determined the initial mathematical models of screening freshmen applicants for Bachelor of Science in Applied Statistics (BSAS) and Bachelor of Science in Information Technology (BSIT) programs based on their input variables such as IQ and prior achievements in English, Mathematics and Science. It also investigated the impacts of these variables on the students’ college first semester performances during SY 2011-2012. The respondents were classified and profiled based on their data and corresponding models were formulated using Discriminant Analysis method. The difference of the respondents’ college performances were tested using T-test. The profile of the BSIT students showed that group1 has higher IQ and lower grades while group 2 has lower IQ but higher grades. The model yielded showed that grade in Science has the stronger discriminating power. IQ has still the greatest discriminating power. The model’s Y-value of 84.86 serves as the reference value. Group 1 has Y-values higher than 84.86 while group 2 has Y-values lower than 84.86.The profile of the BSAS students showed that, except for their IQ, the two groups are not completely separated. The model showed that grades in English and Mathematics have stronger discriminating powers, next to IQ which has the greatest discriminating power. The model’s Y-value is 104.03 and group 1 has Y-values higher than 104.03 while group 2 has Y-values lower than 104.03. In both BSIT and BSAS, groups 1 and 2 showed no significant difference in their first semester college performances, indicating that at the moment group assignment is yet to be a determinant of academic achievement. The primary implication of the study is that screening can be made objective, efficient and cost-saving by mathematically modeling the process.