Lecturer, FOI
Jelena Gusić Munđar is a lecturer at the University of Zagreb Faculty of Organization and Informatics, Department of Quantitative Methods. She graduated Mathematical Statistics at Faculty of Science, Department of Mathematics, University of Zagreb (master degree) and currently she is doctoral student at Interdisciplinary doctoral programme in Statistics, University of Ljubljana. Also, she is member of Learning and Academic Analytics Lab at Faculty of Organization and Informatics, Croatian Statistical Association, Croatian Biometric Society and Croatian Operational Research Society. Her primary interests are multivariate statistics, applied statistics and social network analysis. She is an associate in courses related with statistics, probability and business analytics and currently active member of project HELA (Improving HEI maturity to implement learning analytics).
This lecture provides a concise overview of utilizing logistic regression and decision tree analysis within the SPSS software platform (R or RStudio). Logistic regression is a statistical method used to model binary or categorical outcomes, while decision trees are a popular technique for classification and prediction tasks. Through the SPSS (or R and RStudio) interface, students’ will implement both techniques to explore relationships between variables and make informed decisions based on data-driven insights. This lecture describes how to use SPSS (R and RStudio) for logistic regression and decision tree analysis practically, emphasizing each tool's advantages and possible uses in the business.