Quantitative and Qualitative Methods in Management Sciences and Economics 223191-D
Laboratorium (LAB) Semestr zimowy 2024/25

Overview of common research approaches and methods in management and economics including discussion of distinctions between exploratory and explanatory approaches, qualitative and quantitative studies, descriptive and causal designs, cross-sectional and longitudinal research, investigation of primary and secondary sources.

Developing conceptual framework of a study, including researching background with secondary sources, identifying research problem and research questions, identifying relevant variables for the study, constructing analytical model depicting pertinent relationships between variables and defining hypotheses.

Introduction to qualitative methods: overview of popular techniques and approaches, typical applications and methods of reasoning with qualitative data.

Focus group interview: guidelines for planning and moderating focus groups, designing research study using focus groups as stand-alone technique and introduction to quantitative research, developing moderator's outline, basics of focus group data analysis.

Depth interviews and projective techniques: organizing and conducting depth interviews, using probing techniques, designing and implementing projective techniques, analyzing data from depth interviews and projective techniques.

Types of survey designs: cross-sectional vs. longitudinal surveys, review of merits and faults of different questionnaire administration modes. Questionnaire design: general principles and primary scales of measurement, developing and evaluating multi-item scales. Sampling methods in survey research.

Coding and entering raw data into statistical software. Checking data for consistency and errors. Labeling variables for further research. Frequency distributions, descriptive statistics, presenting data with tables and graphs.

Introduction to inferential statistics and hypotheses testing. Studying associations with cross-tabulations, chi-square test and Cramer's V, variable transformations.

Bivariate correlations: Spearman's rho, Kendall's tau and Pearson's R. Comparing means with t-tests and one-way ANOVA.

Two-way ANOVA, ANCOVA and nonparametric equivalents to ANOVA (Kruskal-Wallis test and median test).

Bivariate and multiple regression modelling.

Exploratory factor analysis.

Binary logistic regression.

Objectives and applications of time series analysis, sources of data for time series analysis in economics. Basic patterns in time series data, smoothing horizontal trends with moving averages.

Linear regression with time series data. Basic polynomial models in time series data. Overview of log-linear models in time series data.