Type:
Bachelor
Speciality:
056201.02.6 - Statistics
Specialisation:
056201.02.6 - Applied statistics and data science
Qualification awarded:
Bachelor of Applied Statistics and Data Science
Programme academic year:
2024/2025
Mode of study:
Full time
Language of study:
Հայերեն
1. Admission criteria/requirements
"Order of admission to RA state and non-state higher educational institutions (according to the bachelor's program)", RA Government Decision (April 7, 2022 N 476-Н)
The entrance exams are:
1. mathematics - competitive,
2. physics or English - competitive,
3. Armenian language and literature - non-competitive.
The entrance exams are:
1. mathematics - competitive,
2. physics or English - competitive,
3. Armenian language and literature - non-competitive.
2. Programme Objectives
● prepare researchers in the fields of modern statistics who will be able to solve applied problems using mathematical methods and computer technologies,
● develop students’ knowledge and skills for different purposes, such as processing massive data emerging from business, engineering, biotechnology and other fields.
● develop students’ knowledge and skills for different purposes, such as processing massive data emerging from business, engineering, biotechnology and other fields.
3. Educational outcomes of the programme
Upon completion of the course, the student will be able to:
- reproduce the basics of probability theory and mathematical statistics,
- present the ways of building software systems with a modeling orientation,
- apply probabilistic and statistical methods to solve scientific problems,
- apply statistical methods for data analysis, processing and decision-making,
- analyze and apply probabilistic models in science.
- apply mathematical methods to solve professional problems,
- build statistical models for problems arising in various fields, examine the database and draw conclusions based on them,
- build effective algorithms to solve various problems with the help of programming tools,
- use mathematical programming packages (Matlab, Matematica, R-programming) for solving theoretical and applied problems,
- apply the methods of mathematical statistics in econometric problems,
- apply R-programming statistical packages for solving applied statistics problems.
- use various sources to get the necessary information,
- coordinate and analyze the received professional information and make conclusions,
- process the received data and make conclusions, participate in discussions, argue and present the received results,
- communicate in writing and orally in native and foreign languages with the professional community,
- continue education in master's degree in financial and actuarial mathematics, information technologies, programming, computer sciences, economics.
4. Assessment methods
The assessment includes the following components:.
1. evaluation of mastery of subsections of the course (educational module) during the semester (2 current exams),
2. ongoing inspections of individual topics of the course (study module) during the semester,
3. verification and assessment of the implementation and assimilation of independent tasks provided by the program during the semester (independent work),
4. evaluation of the independent and/or group research work planned by the program during the semester (research work that replaces any of the current exams),
5. assessment of participation in the course (participation),
6. the final assessment of the entire course (study module) in the examination period which implies an assessment of the level of achievement of the educational outcomes set for the course.
According to the assessment form, the courses are divided into 4 groups: with final assessment, without final assessment, without current exam assessment and with test.
1. evaluation of mastery of subsections of the course (educational module) during the semester (2 current exams),
2. ongoing inspections of individual topics of the course (study module) during the semester,
3. verification and assessment of the implementation and assimilation of independent tasks provided by the program during the semester (independent work),
4. evaluation of the independent and/or group research work planned by the program during the semester (research work that replaces any of the current exams),
5. assessment of participation in the course (participation),
6. the final assessment of the entire course (study module) in the examination period which implies an assessment of the level of achievement of the educational outcomes set for the course.
According to the assessment form, the courses are divided into 4 groups: with final assessment, without final assessment, without current exam assessment and with test.
5. Graduates future career opportunities
Graduates can work
● in any bank, particularly in risk management departments, as financial and statistical analysts;
● in all those institutions (government institutions, commercial organizations, etc.) that have analytical or information technology departments.
● in any bank, particularly in risk management departments, as financial and statistical analysts;
● in all those institutions (government institutions, commercial organizations, etc.) that have analytical or information technology departments.
6. Resources and forms to support learning
Printed, electronic, internet literature, computer rooms.
7. Educational standards or programme benchmarks used for programme development
1. RA National Framework of Qualifications, approved by RA Government Resolution N 714-N of July 7, 2016.
2. "Mathematics" sectoral framework of qualifications, 2022.
3. European Qualifications Framework, 2008.
Undergraduate applied statistics and data science curricula from Moscow, St. Petersburg, and leading Western universities were used.
2. "Mathematics" sectoral framework of qualifications, 2022.
3. European Qualifications Framework, 2008.
Undergraduate applied statistics and data science curricula from Moscow, St. Petersburg, and leading Western universities were used.
8. Requirements for the academic staff
1.General skills
● Teaching/pedagogical the ability to make a course work program (calendar plan),
● knowledge of interactive teaching methods, ability to use active learning techniques.
Research
● the ability to work with various scientific sources, as well as to use Internet information resources,
● ability to lead a student research group.
Communication
● ability to communicate orally with the audience,
● ability to present research results in writing,
● knowledge of a professional foreign language.
ICT application
● basic computer (fluency in MS Office package: Word, Excel, Power-Point) skills,
● skills in making and presenting light shows.
Other skills
● compliance with the norms of professional ethics,
● the ability to estimate the necessary resources and implement projects effectively;
● ability to plan and manage time resources.
2. Professional abilities
● Mastery of the professional subjects of the statistics undergraduate program
● Thorough knowledge of the taught module
● Mastery of key concepts of modules related to the taught module
● Ability to include a research component in the course
● Ability to manage a thesis
3. General requirements
Academic degree
● degree or master's degree in statistics or related field;
● availability of at least 2 scientific and/or methodological publications in the last 5 years,
● participation in conferences and/or workshops in the last 5 years.
Pedagogical experience
● participation in local or international training and/or professional qualification improvement courses during the last 5 years,
Other requirements
Observance of YSU Code of Conduct, the average of grades obtained by the results of the student survey - at least 4.0 (for current professors).
● Teaching/pedagogical the ability to make a course work program (calendar plan),
● knowledge of interactive teaching methods, ability to use active learning techniques.
Research
● the ability to work with various scientific sources, as well as to use Internet information resources,
● ability to lead a student research group.
Communication
● ability to communicate orally with the audience,
● ability to present research results in writing,
● knowledge of a professional foreign language.
ICT application
● basic computer (fluency in MS Office package: Word, Excel, Power-Point) skills,
● skills in making and presenting light shows.
Other skills
● compliance with the norms of professional ethics,
● the ability to estimate the necessary resources and implement projects effectively;
● ability to plan and manage time resources.
2. Professional abilities
● Mastery of the professional subjects of the statistics undergraduate program
● Thorough knowledge of the taught module
● Mastery of key concepts of modules related to the taught module
● Ability to include a research component in the course
● Ability to manage a thesis
3. General requirements
Academic degree
● degree or master's degree in statistics or related field;
● availability of at least 2 scientific and/or methodological publications in the last 5 years,
● participation in conferences and/or workshops in the last 5 years.
Pedagogical experience
● participation in local or international training and/or professional qualification improvement courses during the last 5 years,
Other requirements
Observance of YSU Code of Conduct, the average of grades obtained by the results of the student survey - at least 4.0 (for current professors).
9. Additional information about the programme
No program on applied statistics is taught in any higher institution in Armenia. There are several programs similar in nature to this topic, but they are all implemented in the master's degree.
