Advanced Data Exploration Methods - Dimension Reduction, Exploratory Factor Analysis and Clustering Analysis 2500-PL-PS-SP15-14
Ćwiczenia (CW) Semestr zimowy 2024/25

Student performance will be assessed base on preparation (reading assigned literature and home assignments), class activities (class performance, solving tasks assigned in class, in-class activity) and final test.

 4 homeworks (40%)

 class activities (10%)

 final practical test i.e., solving statistical problems (50%)

Student may have maximum 2 absences.

Block 1) Factor Analysis and PCA, Reliability and creating composite measures.

 Theory, purpose and assumptions

 Screening data prior to analysis

 Types of analysis – extraction, rotation, methods for determining number of factors / components (and methods to choose one appropriate for data)

 Interpretation of obtained results

Block 2) Clustering

 Utility of clustering methods in social sciences

 Different methods and types of clustering (disjoint, hierarchical and overlapping)

 interpretation and validity of results

Block 3) Multidimensional scaling

Course will with the use of students’ own computers. Students should have SPSS installed, as most of the exercises will require this program. Most of the class activities will be in form of in class exercises. Students are required to participate in lectures and short in-class discussions, solve prepared theoretical tasks and complete homeworks (4 per semester).