Széchenyi 2020
Budapesti Corvinus Egyetem ×

Institute of Mathematics and Statistical Modeling

Economical modelling has a long standing history within the University, mainly centered around the Institution (and it’s legal predecessors). The task of economical modelling is diverse, the accomplishments of the Institution’s staff are regarded as a benchmark reference in many areas.  

We cultivate the following areas, among others:

  • mathematics; analysis essential for producing economic and social analyses; probability calculation; studying and application of algebra;
  • descriptive and inferential statistics; and econometrics, which is one of the cornerstones of virtually any quantitative analysis for economic or business purposes;
  • actuarial sciences, including not only insurance mathematics in its narrow sense, but also demography, financial models of insurance contracts, and the use of statistics for insurance purposes;
  • game theory, in the development of which both mathematics and economics play a decisive role;
  • operations research, which aims to use resources efficiently;
  • data analysis, which means, among others, the use of information available within a company for business purposes;
  • narrower areas include stochastics of financial processes; quantitative models of energetics; models of national accounts; price models; welfare research; spatial analyses (Spatial Statistics).


 
Numerous studies in the field of economic modelling have been published in the most prestigious international journals. Educational activities are of two layers, on the one hand, we teach a wide range of methodological subjects that are essential for studying economics; and, on the other hand, we satisfy the needs, in a methodologically sound manner, of students who are interested in serious and deep mathematics, statistics, operations research, and data analysis. 

Events, success stories, and what we are proud of

Research Seminars at the Institute

Topic: MSMI research seminar: Szabina Fodor, Réka Vas, László Kovács

Time: Feb 11, 2022 01:30 PM

Meeting ID: 872 6767 4654

Passcode: 888142

Abstract

Modelling students’ performance is one of the  most  challenging and exciting research  areas of data  analytics  in higher  education.  This performance is  influenced by  multiple  factors  and  is  not accurately  measured by  the traditional  five-point  scale  thus  making this  field attractive.  The  widespread availability  of  educational  datasets  further  catalyses  its  popularity. In the present work, the authors  investigate the performance of students  starting their studies in the autumns of 2011, 2012, and 2013 at Corvinus  University  of  Budapest, in the undergraduate business informatics training program, using variables available from the Neptun Education   System.  To accurately  measure student performance, a new  metric was developed that describes student performance on  a broader  set of  values  than the traditional  five-point  grade.   This new metric  is used  to investigate  the  correlations between  students’ performances in subjects,  applying  structural equation models (SEM). The results  show that through SEM, substantial relationships can be  revealed  between the investigated  courses. A proper,  interdependent system  of prerequisites in the  curriculum  may  be developed based on these results.   The methodology  presented in  this study  can also  be  used to anticipate possible difficulties students may  face in  terms of certain subjects and  to  offer  tailored help.









Data Analysis in Practice Lecture Series


Optimization Seminar

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GEN.:2022.08.14. - 22:29:09