CSIE_analysis_ASE5
by Irimia Mihaela
2025-09-23
Academic profiles of rejected and absent candidates
Warning: The dataset analyzed in this study is not an official list provided by ASE and was created based on the information available on site.
This study examines the admission outcomes of candidates applying to ASE master’s programs across 12 faculties, namely:
Facultatea de Business și turism (BT)/Faculty of Business and tourism
Facultatea de Contabilitate și informatică de gestiune (CIG)/Faculty of Accounting and management information systems
Facultatea de Cibernetică, statistică și informatică economică (CSIE)/Faculty of Cybernetics, statistics and economic informatics
Facultatea de Drept (DA) /Faculty of Law
Facultatea de Economie teoretică și aplicată (ETA)/Faculty of Theoretical and applied economics
Facultatea de Finanțe, Asigurări, Bănci și Burse de Valori (FABBV)/Faculty of Finance, insurance, banking and stock exchange
Facultatea de administrarea afacerilor cu predare în limbi străine (FABIZ)/Faculty of Business administration in foreign languages
Facultatea de Management (MAN)/Faculty of Management
Facultatea de Marketing (MRK)/Faculty of Marketing
Facultatea de relații economice internaționale (REI)/Faculty of International business and economics.
By analyzing the available data on ASE, master admission, Decision No. 89/14.05.2025 platforms, we aim to identify patterns of academic performance, compare results across faculties, and explore potential factors that influences the competitiveness among applicants.
Objective The objective of this analysis is to examine the profiles of rejected and absent candidates, focusing on their bachelor’s exam grades and admission test scores, in order to understand the factors influencing rejection or non-participation and to assess the competitiveness and selection mechanisms within each faculty.
The analysed variables are presented below:
## Rows: 4,392
## Columns: 16
## $ nr_crt <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,…
## $ cod_candidat <dbl> 4397, 1068, 1726, 1670, 1841, 2369, 2372, 1681, 1078, …
## $ proba_scrisa <dbl> NA, 84, 84, 81, 78, 78, 78, 84, 75, 75, 75, 75, 75, 72…
## $ medie_concurs <dbl> NA, 9.76, 9.76, 9.64, 9.52, 9.52, 9.52, 9.46, 9.40, 9.…
## $ medie_licenta <dbl> 9.00, 10.00, 10.00, 10.00, 10.00, 10.00, 10.00, 9.50, …
## $ statut <chr> "Standard", "Standard", "Standard", "Standard", "Stand…
## $ rezultat <chr> "Absent", "Admis", "Admis", "Admis", "Admis", "Admis",…
## $ forma_invataman <chr> "Absent", "Buget", "Buget", "Buget", "Buget", "Buget",…
## $ specializare <chr> "EAM1", "EAM1", "EAM1", "EAM1", "EAM1", "EAM1", "EAM1"…
## $ program <chr> "Economia si administrarea afacerilor agroalimentare, …
## $ facultatea <chr> "Economie Agroalimentara si a Mediului", "Economie Agr…
## $ pob <dbl> 187, 187, 187, 187, 187, 187, 187, 187, 187, 187, 187,…
## $ pot <dbl> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, …
## $ nlb <dbl> 182, 182, 182, 182, 182, 182, 182, 182, 182, 182, 182,…
## $ nlt <dbl> 36, 36, 36, 36, 36, 36, 36, 36, 36, 36, 36, 36, 36, 36…
## $ ntl <dbl> 218, 218, 218, 218, 218, 218, 218, 218, 218, 218, 218,…Our dataset contains 16 variables — 10 numeric and 6 character — and 5,357 observations.
Main indicators of descriptive statistic
We want to check for duplicates and verify whether a candidate was admitted to more than one program:
The candidate with code 1000 applied to two programs (CSIE4 and CSIE3), but was admitted to only one of them (CSIE4) and so on.
We extract the first option with the biggest final admitted score of each candidate, but in some cases not admitted
## nr_crt cod_candidat proba_scrisa medie_concurs
## Min. : 1.0 Min. :1000 Min. : 0.00 Min. : 4.960
## 1st Qu.: 50.0 1st Qu.:2108 1st Qu.:51.00 1st Qu.: 7.750
## Median :116.0 Median :3002 Median :63.00 Median : 8.440
## Mean :154.2 Mean :2993 Mean :61.88 Mean : 8.365
## 3rd Qu.:249.0 3rd Qu.:3930 3rd Qu.:75.00 3rd Qu.: 9.070
## Max. :489.0 Max. :4827 Max. :90.00 Max. :10.000
## NA's :327 NA's :327
## medie_licenta statut rezultat forma_invataman
## Min. : 6.000 Diaspora : 73 Absent : 327 Absent : 327
## 1st Qu.: 8.660 Dizabilitati : 9 Admis :3369 Buget :1886
## Median : 9.330 Minoritati : 1 Respins: 696 Respins: 697
## Mean : 9.166 ProtectieSociala: 3 Taxa :1482
## 3rd Qu.:10.000 Rom : 3
## Max. :10.000 Standard :4303
##
## specializare program
## Length:4392 Length:4392
## Class :character Class :character
## Mode :character Mode :character
##
##
##
##
## facultatea pob
## Cibernetica, Statistica si Informatica Economica :1017 Min. : 0.0
## Relatii Economice Internationale : 458 1st Qu.: 72.0
## Administrarea Afacerilor cu predare in limbi straine: 439 Median :187.0
## Marketing : 413 Mean :199.4
## Management : 406 3rd Qu.:339.0
## Contabilitate si Informatica de Gestiune : 402 Max. :361.0
## (Other) :1257
## pot nlb nlt ntl
## Min. : 0.00 Min. : 0.0 Min. : 0.0 Min. : 29.0
## 1st Qu.: 1.00 1st Qu.: 39.0 1st Qu.: 32.0 1st Qu.: 54.0
## Median : 4.00 Median :106.0 Median : 75.0 Median :218.0
## Mean :12.16 Mean :105.5 Mean :116.7 Mean :222.2
## 3rd Qu.:12.00 3rd Qu.:123.0 3rd Qu.:226.0 3rd Qu.:328.0
## Max. :68.00 Max. :246.0 Max. :409.0 Max. :567.0
## Rejected candidates
Bachelor score
The mean value of the bachelor score only for the rejected candidates
Admission test score
The mean value of the admission test score only for the rejected candidates
Final admission score
The mean value of the final admission score only for the rejected candidates
Absent candidates
The mean value of the bachelor score only for the absent candidates Distribution of bachelor score by each faculty
Conclusions
In the case of the distributions of rejected candidates based on their bachelor’s graduation grades, we observe that most are left-skewed, suggesting that the majority of rejected candidates had high grades in their final exams. In some cases, the distributions are leptokurtic, indicating very small differences between candidates. We also notice that not all faculties have rejected candidates, which means that either all places were filled or some remained available for the autumn admission session.
The graduation grades of the rejected candidates are generally high, ranging between 8.47 (Law) and 9.49 (Business and tourism), values comparable to those of admitted candidates. This suggests that rejection may be due either to increased competition or to the rule that a candidate can only be admitted to one study program, based on their final admission score, regardless of the number of options submitted.
Therefore, rejection does not reflect a lack of preparation on the part of the candidates, but is rather related to the selection mechanism: each candidate can only be admitted to one specialization within the faculty, based on the final admission score. Rejections occur when the chosen program is not the candidate’s first option, when the admission test score is not high enough, when competition is very intense, or when the number of available places is limited. The differentiation between candidates is primarily based on the admission test score, which plays a key role in ranking and selection process.
Compared to the grades obtained in the bachelor’s exam, the admission test scores allow for a clearer differentiation between candidates. Regarding the distributions of candidates by admission test scores, we observe that some are left-skewed and leptokurtic, which suggests that candidates achieved above-average scores that are closely concentrated. At the same time, some faculties show right-skewed and platykurtic distributions, confirming that candidates’ scores are below average and performance levels are more diverse.
The faculty of Business administration in foreign languages records the highest average admission test score, indicating strong competitiveness and better-prepared candidates. In contrast, at the faculties of Marketing and Cybernetics, statistics, and economic informatics, the admission test scores are much lower, pointing to weaker preparation and greater variability among candidates. Here, the selection mechanism is clearer, as the differences between admitted and rejected candidates are more evident.
Most candidates who did not attend the admission exam had high bachelor’s grades. Most of the distributions are left-skewed, confirming that their bachelor’s grades were above average. In addition, most distributions are platykurtic, indicating differences among candidates. Their absence from the admission test may be explained by several factors, such as: a change in decision regarding the chosen study program, participation in admission exams organized by other universities, the inability to attend the written test, or simply a lack of interest.
Also, in this case, the differentiation between candidates is made through the admission test and/or the specialized interview in which candidates are required to participate during the exam process.
References
- T. Pals, Research Finds that High School GPAs Are Stronger Predictors of College Graduation than ACT Scores, https://www.aera.net/Newsroom/Research-Finds-that-High-School-GPAs-Are-Stronger-Predictors-of-College-Graduation-than-ACT-Scores?utm_source=chatgpt.com, 2020.
- https://research.collegeboard.org/media/pdf/SAT_Score_Relationships_with_College_Degree_Completion.pdf?utm_source=chatgpt.com, accesat la 23.08.2025.
- https://ase.ro/comunicare/noutati/regulamentul-admitere-masterat-2025-2026/, accessed on 04.08.2025.
- https://ase.ro/admitere/masterat/, accessed on 28.07.2025.
- Decision No. 89/14.05.2025, accessed on 04.08.2025