Prediction of master student influx in the faculty of science

Abstract

This research will focus on making a prediction of student influx in 2022 for some of the masters from the faculty of science that are offered at Utrecht University. In this thesis, the number of enrolments in September 2022 for the master programmes Artificial Intelligence (AINM), Experimental Physics (EXPH) and Business Informatics (MBIM) is predicted using a Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors (SARIMAX) model. The deadline for applying for these masters is June first and the number of enrolments is known in September, but it would be best to know the number of starting students as early as possible so e.g. staff can be hired and schedules can be made in advance. SARIMAX is first used at the start of May to predict the total number of applications and this number is then used as external variable for SARIMAX, that also takes the number of applications and enrolments of previous years into account. The predicted number of enrolling students for AINM, EXPH and MBIM based on all applications is 76, 15 and 49 respectively. The 95% confidence intervals, so the expected minimum and maximum number of enrolments [min, max], are [59, 94], [0, 32] and [32, 66] students respectively for the three master programmes. While these numbers give an indication of the number of students that can be expected to show up in September, the predicted range is still broad and so it might be difficult for Utrecht University to make decisions based on these predictions. Furthermore, when making influx predictions before the deadline, using a prediction of the final number of applications, the confidence interval gets even bigger so making precise predictions before June first is even more difficult.