• The nature of economic research and its basic limitations, forms of research (descriptive, experiment, ...)
• Formulation of problems, research questions, hypotheses and their operationalization, validity and reliability of variables
• Population and sample decisions, representativeness and sample weights
• The importance of pilot studies, their forms, sources of information for these studies
• Sources of statistical data, data collection techniques (observation, interview, questionnaire, document analysis, ...) and their limitations
• Design of data gathering tools (observation sheets, questionnaire, ...), principles of questions formulation, verification of data gathering tools
• Data gathering and preparation for further processing (data control, preparation of variables, missing observation problem, etc.)
• Types of variables (categorical, ordinal, interval), basic methods of statistical analysis (crosstables, Chi2 test, correlation)
• Basic methods of statistical analysis (hypothesis testing, cluster analysis, factor analysis)
• Principles of writing analyses, types of research outputs (monograph, article, research report, study, ...), formal requirements and citation standards
• Academic writing (structure of written text, content of individual parts of the analysis, principles of written speech)
• Graphic representation of information, charts and figures
• Principles of presentation of research results (preparation of presentation, verbal speech, non-verbal speech)
• Statistical Data Analysis Software (STATA, R, SPSS)
• Formulation of problems, research questions, hypotheses and their operationalization, validity and reliability of variables
• Population and sample decisions, representativeness and sample weights
• The importance of pilot studies, their forms, sources of information for these studies
• Sources of statistical data, data collection techniques (observation, interview, questionnaire, document analysis, ...) and their limitations
• Design of data gathering tools (observation sheets, questionnaire, ...), principles of questions formulation, verification of data gathering tools
• Data gathering and preparation for further processing (data control, preparation of variables, missing observation problem, etc.)
• Types of variables (categorical, ordinal, interval), basic methods of statistical analysis (crosstables, Chi2 test, correlation)
• Basic methods of statistical analysis (hypothesis testing, cluster analysis, factor analysis)
• Principles of writing analyses, types of research outputs (monograph, article, research report, study, ...), formal requirements and citation standards
• Academic writing (structure of written text, content of individual parts of the analysis, principles of written speech)
• Graphic representation of information, charts and figures
• Principles of presentation of research results (preparation of presentation, verbal speech, non-verbal speech)
• Statistical Data Analysis Software (STATA, R, SPSS)