Study program / study programs: Advanced data analytics
Course: Analysis of International Research Datasets
Teacher(s): Jelena Pešić, Irena Petrović, Jelisaveta Petrović, Dragan Stanojević, Oliver Tošković
Course status: Elective
ECTS points: 7
Prerequisites: Knowledge of basic statistical analysis techniques; skilled in SPSS
Course objective:
Introduction to analysis of data from international official statistics and comparative social research databases and datasets.
Learning outcomes:
Getting acquainted with different international comparative databases (macro- and micro-data). Critical evaluation of reliability, validity and comparability of international comparative data.
Mastering the application of techniques of statistical analysis on international comparative data.
Mastering analytical skills in usage of international and comparative data in solving different social problems and designing policies.
Course structure and content:
Secondary data analysis. Introduction to different types of international statistical and academic databases and data. Critical evaluation of data: validity, reliability and comparability. 
Overview of international comparative macro-data. Data on economic development (World Bank, UN – HDI, OECD, Structural Business Statistics – EUROSTAT, Global Entrepreneurship Monitor, etc.). Data on poverty and social exclusion (EUROSTAT, CEPAL). Gender Statistics (EIGE, UN Woman, etc.).
Overview of international comparative micro-data. European Union Statistics on Income and Living Conditions (EU SILC). European Union Labor Force Survey (EULFS). European Social Survey (ESS). World Value Survey (WVS). International Social Survey Project (ISSP).
Application of techniques of statistical analysis on comparative international micro-data. Topics: Individual and Social Welfare (ESS). General and Institutional Trust (ESS). Attitudes on migration (ESS). Attitudes on Family and Gender Roles (ISSP). Attitudes on Work  (ISSP). Attitudes on Social Inequalities (WVS). Political Participation (WVS).
Literature/Readings:
Kiecolt & Nathan, 1990: Secondary Data Analysis, Sage University Papers
MacInnes, John, 2017: An Introduction to Secondary Data Analysis With IBM SPSS Statistics, Sage
Smith, Emma, 2008: Using Secondary Data in Education and Social Research, Mc Graw Hill Open University Press
Jasna Soldić-Aleksić, 2015: Primenjena analiza podataka. Rad u programima za statističku analizu i tabelarna izračunavanja, Ekonomski fakultet, Beograd
Republički zavod za statistiku, 2017: Anketa o radnoj snazi, BeogradEUROSTAT, 2018: Statistical cooperation – introduction (https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Statistical_cooperation_-_introduction)
EUROSTAT, 2018: EU statistics on income and living conditions (EU-SILC) methodology (https://ec.europa.eu/eurostat/statistics-explained/index.php/EU_statistics_on_income_and_living_conditions_(EU-SILC)_methodology)
The number of class hours per week:
Lectures: 5
Labs: 0
Workshops: 1
Research study: 2
Other classes: 0
Teaching methods:
Individual and group work; lectures and labs.
Evaluation/Grading (maximum 100 points):
Pre-exam requirements (Power point presentations of small research tasks): 40
Final exam (Research paper – application of statistical techniques on analysis of comparative data): 60
Pre-exam requirements