CSIE_analysis_ASE6
by Irimia Mihaela
2025-09-23
Academic profiles of ASE 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 evaluate the academic performance of candidates who were registered, admitted, admitted to both tuition-free and tuition-fee places, and rejected across ASE faculties. The study highlights differences in competitiveness, score distributions, and the homogeneity of admitted groups. It aims to identify the most competitive faculties, where candidates achieve high and closely clustered results, and to contrast them with faculties where performance is more heterogeneous and selection is less stringent.
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
## Descriptive index’s for …
Bachelor score variable
Registered candidates
Admitted candidates
Tuition free candidates
Tuition fee candidates
Rejected candidates
Admission test score variable
Registered candidates
Admitted candidates
Tuition free candidates
Tuition fee candidates
Rejected candidates
Final admission score variable
Registered candidates
Admitted candidates
Tuition free candidates
Tuition fee candidates
Rejected candidates
Boxplots of candidates scores
Bachelor score
Bachelor score distribution across faculties, categorized by admission result (registered, admitted – tuition-free/tuition-fee, rejected, absent).
The above chart shows the distribution of bachelor score across different faculties. Faculties like Business and tourism, Marketing and International economic relations tend to have higher medians (closer to 9.5 - 10), whereas faculty like Management, Public administration and Agrofood economics and environment show lower medians (closer to 9 or below). Most faculties have candidates with very high bachelor score, but there are some faculties with bachelor score (outliers) below 7.
Admission test score
Admission test score distribution across faculties, categorized by admission result (registered, admitted – tuition-free/tuition-fee, rejected, absent).
The above chart shows the distribution of admission test score across different faculties. Faculties such as International Economic Relations, Business Administration in Foreign Languages, and Theoretical and Applied Economics tend to have higher medians (closer to 85 - 100), whereas faculty such as Public administration, and Agrofood economics and environment show lower medians (closer to 60 or below). Most faculties include candidates with very low scores, but there are some faculties with admission scores (outliers) below 35.
Final admission score
Final admission score distribution across faculties, categorized by admission result (registered, admitted – tuition-free/tuition-fee, rejected, absent).
The chart above shows the distribution of bachelor scores across different faculties. Faculties such as Business Administration in Foreign Languages, International Economic Relations, and Theoretical and Applied Economics tend to have higher medians (closer to 9.5–10), whereas faculties such as Public Administration and Agro-Food Economics and Environment show lower medians (around 8 or below). Most faculties include candidates with very low final admission scores, and in some cases there are outliers with scores below 7.
Conclusions
The analysis examines candidate performance across ASE faculties, comparing registrations, admissions to tuition-free and tuition-fee places, and rejections. It aims to highlight competitive faculties with high, homogeneous results versus those with more varied performance and less selective admissions.
The analysis shows that Business and tourism, Finance, insurance, banking and stock exchange, and International economic relations attract highly prepared candidates, with median bachelor’s scores between 9.5 and 10. Faculties such as Law and Business and tourism stand out for their competitiveness, as the small interquartile ranges indicate very little variation among candidates. For admitted students, the highest competitiveness is observed in Theoretical and applied economics, Cybernetics, statistics and economic informatics, and Business and tourism, where bachelor’s scores are consistently very high (9.16–10), while in other faculties, performance is more heterogeneous (8.1–10).
For admitted candidates, we observe that the median values are high (between 9 and 10), with the exception of the faculty of Law, where bachelor’s scores are somewhat lower (ranging from 8.1 to 10). Regarding candidates admitted to tuition-free (state-funded) places, most display very high bachelor’s exam scores. Faculties with a high level of competitiveness among candidates include Business and tourism, Theoretical and applied economics, and International economic relations, with the exception of faculties such as Agri-Food and environmental economics, Law, Finance, insurance, banking and stock exchange, or Accounting and management information systems, where differences among students are larger and distributions more heterogeneous.
It can be said that large faculties, which attract a significant number of applicants and present greater variability in bachelor’s exam scores, indicate strong competition for tuition-free places, where the differences among admitted candidates are very small. This trend also applies to fee-paying students: although the differences among them are greater and the average/median bachelor’s score is slightly lower, competition remains high in certain faculties.
It is clear that there is strong competition for tuition-free places, with significant differences between candidates admitted to tuition free versus fee-paying places. In faculties such as Cybernetics, statistics and economic informatics, International economic relations, and Business administration in foreign languages, candidates admitted to tuition-free places typically had bachelor’s scores between 9.3 and 10, while those admitted to fee-paying places often had scores of 8 or even below 8.
The analysis shows that admitted candidates generally have high bachelor’s exam scores (9–10), except at the faculty of Law, where scores are slightly lower (8.1–10). For tuition-free places, competition is strongest in Business and tourism, Theoretical and applied economics, and International economic relations, where differences among candidates are minimal.
By contrast, faculties such as Law, Finance, banking, and insurance, Accounting, and Agri-Food and environmental economics display more heterogeneous distributions, with larger gaps between candidates. Larger faculties attract more applicants with diverse performance levels, but competition for tuition-free places remains intense, as only top candidates (often 9.3–10) are admitted.
For fee-paying places, the average and median scores are slightly lower, and differences among candidates are greater, yet competition persists. In some faculties (e.g., Cybernetics, International economic relations, Business administration in foreign languages), a clear distinction emerges: tuition-free candidates score 9.3–10, while fee-paying candidates are admitted with scores closer to 8 or below.
Regarding the distributions of admitted candidates based on their admission test scores, we observe that the differences between them are very small. At the faculties of [International economic relations and [Business administration in foreign languages, candidates obtained scores above 8.
The faculties with the highest level of competitiveness among candidates for both tuition-free and fee-paying places are Business administration in foreign languages and International economic relations. We also note differences between the distributions of candidates admitted to tuition-free places and those admitted to fee-paying places. Among fee-paying candidates, the differences are generally very small, except in the faculties of Finance, banking, and insurance, Law, and International economic relations, where the differences between candidates are somewhat larger and the distribution is more heterogeneous.
The distributions of candidates based on their admission averages are presented the same trend: the top faculties remain Business administration in foreign languages , Theoretical and applied economics , Business and tourism , and International economic relations , where candidates are admitted with high admission scores.
The most popular faculties are Business and tourism , Theoretical and applied economics , and International economic relations , which attract very well-prepared candidates with excellent bachelor’s exam results. This indicates that demand for the study programs offered by these faculties is very high.
Candidates enrolled in the faculties of International eonomic relations, Business and tourism, Theoretical and applied economics, and Cybernetics, statistics and economic informatics are academically very similar, with most of them achieving high and closely comparable grades. This situation increases competitiveness and makes the selection process more challenging. The popularity of these programs can be explained by their international recognition and strong labor market outcomes, which tend to attract highly prepared candidates. 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.
At the opposite side, the faculties of Law, Agri-Food and anvironmental economics, and Accounting and management information systems register larger differences between candidates. Here, the student populations are more heterogeneous, which makes the selection process easier, as the differentiation between candidates is more evident.
We observe that the highest mean and median values are recorded in the faculties of Business administration in foreign languages, International economic relations, Business and tourism, and Theoretical and applied economics, while the smallest differences among candidates are found in Public administration and management, Theoretical and Applied Economics, and Business and tourism.
Regarding the average scores of admitted candidates, the trend remains consistent; however, the highest level of competitiveness is seen in Cybernetics, statistics and economic informatics, Business administration in foreign languages, and Theoretical and applied economics.
Moreover, a clear distinction emerges between students admitted to state-funded places and those admitted to tuition-based places: the latter show visibly lower averages, indicating that tuition-based admission serves as an alternative for candidates who did not qualify for state-funded places but still wish to pursue their studies.
Finally, the IQR values are smaller for most programs in the case of state-funded admissions, reflecting more homogeneous groups of students, closer in terms of preparation level and thus facing greater competition. In contrast, candidates admitted to tuition-based places are more heterogeneous, showing wider variability in academic performance.
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