Monographic lecture: Use of data mining algorithms in psychology: cluster analysis WF-R-PS-WMAD
1. Introduction to Generalized k-means Cluster Analysis algorithms, basic information about the method
2. Basic information on the operation of the algorithm: grouping the subjects into clusters.
3. Basic information on how the algorithm works: calculating differences between clusters.
4. Basic information on the operation of the algorithm: determining the results of people in clusters on the basis of the normalized mean.
5. Conducting a cluster analysis and reporting the results - exercise 1.
6. Conducting a cluster analysis and reporting the results - exercise 2.
7. Conducting a cluster analysis and reporting the results - exercise 3.
8. Basic assumptions of modeling with systems of structural equations
9. Calculation of the first model using the system of structural equations in AMOS.
10. Calculating cluster analysis for variables from the structural model. Determining the characteristics of clusters in terms of variables.
11. Calculation of the second model using the system of structural equations in AMOS.
12. Calculating cluster analysis for variables from the second structural model. Determining the characteristics of clusters in terms of variables.
13. Plotting a theoretical curve.
14. Plotting an empirical curve based on the results of cluster analysis.
15. Estimating the fit of the empirical curve to the theoretical curve.
(in Polish) Grupa przedmiotów ogólnouczenianych
Subject level
Learning outcome code/codes
Type of subject
Course coordinators
Learning outcomes
KNOWLEDGE:
- PhD students correctly use the terminology of the cluster analysis method, have knowledge of how to classify objects, normalized mean, etc.
SKILLS:
- students carry out cluster analysis with the use of algorithms
COMPETENCES:
- students correctly interpret the results of the analysis
Description of ECTS credits
Participation in classes: 30 hours
Preparation for classes and preparation of reports, reading literature: 30 hours
Assessment criteria
The basis for completing the course is submitting the final report presenting the results prepared using the cluster analysis method
Bibliography
Elder, J., Hill, T., Miner, G., Nisbet, B., Delen, D., & Fast, A. (2012). Practical Text Mining and Statistical Analysis for Nono-structured Text Data Application. Oxford: Elsevier.
Nisbet, R., Elder, J., & Miner, G. (2009). Handbook of statistical analysis and data mining applications. Burlington, MA: Academic Press (Elsevier).
Szymańska, A. (2017b). Wykorzystanie analizy skupień metodą data mining do wykreślania profili osób badanych w badaniach psychologicznych [Using cluster analysis in the data mining method to draw profiles of participants surveyed in psychological research]. Studia Psychologiczne, 55(1), 25–40.
Additional information
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