Program Overview

Survey Statistics and Data Analytics MSc

The Survey Statistics and Data Analytics MSc program is designed to train data analysts who can contribute to data-driven decision making in business, industry, public administration, or social research. The program aims to provide students with the skills to analyze large databases, be familiar with statistical solutions for survey-based research, and conduct online research and web analytics in scientific, governmental, and business applications.

Program Details

• Title: Survey Statistics and Data Analytics MSc
• Degree: Survey Statistician and Data Analyst
• Type: Degree program
• Level: Master
• Accreditation number: MSZKSUR
• Faculty: Faculty of Social Sciences
• Institute: Institute of Empirical Studies
• Department: Department of Statistics
• Language: English
• Duration: 4 semesters (2 years)
• ECTS credits: 120
• Minimum number of students: 10
• Maximum number of students: 25

Description

The program focuses on training data analysts who can contribute to data-driven decision making in various fields. Students will gain knowledge of network analysis, natural language processing, and the basics of machine learning. They will be prepared to implement analytic solutions in R and Python and know the basics of data analysis infrastructure (SQL, Git, and other tools).

Tracks/Specializations

There are no specializations, but students can tailor their learning path to their own interests as the electives are organized into the following modules of two to three courses:

• Biomedical Research
• Economic Research
• Digital Data Analytics
• Social Research
• Business Research

Strength of Program

The program has been running successfully in Hungarian for 30 years and is one of the most popular master's programs at ELTE. Its founder is Tamás Rudas, Professor at the Department of Statistics at the University of Washington. The program's success is based on continuous improvement and adaptation to changing social contexts.

Modular Programme Structure

The program is divided into 5 mandatory blocks:

• Mathematical foundation (mathematical foundation, linear algebra, probability theory, mathematical statistics)
• Data collection (data collection methods and sampling, survey data processing)
• Basics of business research (market research, communication and project management, project practice)
• Programming (R, Python, Github, SQL)
• Data analysis (multivariate probability theory and statistics, data science, data analysis)
• Applications (qualitative research, social studies, network analysis)

Elective Professional Modules

In addition to the mandatory modules, the program offers differentiated professional modules with elective courses:

• Biomedical Research
• Economic Research
• Digital Data Analytics
• Social Research
• Business Research

Career Opportunities

The program has the advantage of adapting to the complex needs of the labor market. Graduates can design research based on either questionnaire, digital or administrative data sources. They will have the opportunity to develop a learning path and career path that suits their own interests.

Job Examples

• Data Scientist
• Business Intelligence Analyst
• Survey Statistician
• Healthcare Analyst
• Data Analyst

Tuition Fee

• EU/EEA students: 1550 EUR per semester
• non-EU/EEA students: 3500 EUR per semester

Application Fee

• EUR 50 (non-refundable) between 01/10/2025-11/2025
• EUR 100 (non-refundable) between 20/11/2025-01/2026
• EUR 150 (non-refundable) between 20/01/2026-04/2026
• EUR 200 (non-refundable) between 05/05/2026-05/2026

Admission Requirements

Entry Requirements

Applicants must have a BA/BBA degree in any of the following fields: Social Studies, Sociology, Applied Economics, Economic and Financial Mathematical Analysis, Commerce and Marketing.

Language Requirements

Certification of English knowledge (both written and oral): B2

• IELTS Score: 5.5
• TOEFL iBT Band: 46-59
• Cambridge English Scale Score: 162

Application Procedure

The application starts in the online application system. Students need to register in the system, fill in the online application form, upload the required documents, and follow the instructions during the application process.

Documents to Submit with Application

• Online application form
• Bachelor-level degree
• Transcript of records
• Motivation letter
• Copy of the main pages of the passport (needs to be valid)
• Copy of application fee transfer
• Language certificate (if the applicant has one)

Entrance Examination

The application deadline refers to the final submission of the complete application package through the online application system. After each application deadline, the Admission Board reviews the applications. After the admission interview, applicants are informed of the selection outcome through the online application system within approximately one month after the admission interview.

Further Details of the Entrance Exam

During the exam, applicants will have a discussion on one of the topics listed below. The topics are based on Freedman, D. - Pisani, R. - Purves, R.: Statistics, 4th edition. W. W. Norton & Company, 2007 (or later edition). The topics include:

1. Experiments and observational studies
2. Probability: independence, product rule, addition rule, conditional probability
3. Statistical inference: point estimate, confidence interval, why inference is useful, what has an effect on the confidence interval
4. Null hypothesis significance testing: why is it useful, null- and alternative hypothesis, significance level, one- and two-sided tests
5. Z-test, t-test: when are these applied, what is the difference between one- and two-sample (independent samples) tests
6. Chi-square tests: when are these used, what are the assumptions
7. Correlation: what is it used for, what are the assumptions, how to use it
8. Regression: what is it used for, what are the assumptions, how to use it
9. Reliability and validity: what do these mean, what factors influence these
10. Sampling: simple random sampling, two-stage sampling, sampling design and validity, why use two-stage sampling, what is representativity

Program Leader and Coordinator

• Program leader: Dr. Renáta Németh, Professor
• Program coordinator: Ms. Adrienn Dankovics, Departmental Coordinator

International Office

The International Office of the Faculty of Social Sciences provides support for international students. For more information, please contact the International Office.