Advanced Data Exploration Methods - Dimension Reduction, Exploratory Factor Analysis and Clustering Analysis
Informacje ogólne
| Kod przedmiotu: | 2500-PL-PS-SP15-14 |
| Kod Erasmus / ISCED: |
14.4
|
| Nazwa przedmiotu: | Advanced Data Exploration Methods - Dimension Reduction, Exploratory Factor Analysis and Clustering Analysis |
| Jednostka: | Wydział Psychologii |
| Grupy: | |
| Punkty ECTS i inne: |
4.00
|
| Język prowadzenia: | angielski |
| Skrócony opis: |
(tylko po angielsku) The course is intended for students that want to learn methods for exploring data structure. The course will consist of theoretical lecture and followed by practical excercises. The focus of LECTURE part will be on reviewing logic of assumptions, possibilities and limitations of PCA, EFA, MDS and Clustering methods. The focus of WORKSHOP part will be on practical issues such as selecting the appropriate analysis, preparing data for analysis, interpreting output, and presenting results of a complex nature. The primary goal of the course is to develop an applied and intuitive understanding of the covered statistical material. |
| Efekty uczenia się: |
(tylko po angielsku) Students who successfully complete this course will be able to: Understand the latent variable measurement problems that can and cannot be addressed using factor analysis Determine which technique is appropriate for different problems, based on the goals of the research. Explore multivariate data using visualization techniques (including multi-dimensional scaling) to illuminate the structure in the data. For clustering problems, be able to choose a suitable metric and technique, depending on the goals of the research, as well as be aware of the strengths and limitations of the various approaches. For data structure problems, be able to select appropriate method, construct model, run analysis, interpret and report results. |
Zajęcia w cyklu "Semestr zimowy 2023/24" (zakończony)
| Okres: | 2023-10-01 - 2024-01-28 |
 
PN WT ŚR CZ CW
PT |
| Typ zajęć: |
Ćwiczenia, 30 godzin
|
|
| Koordynatorzy: | (brak danych) | |
| Prowadzący grup: | Mikołaj Winiewski | |
| Lista studentów: | (nie masz dostępu) | |
| Zaliczenie: |
Przedmiot -
Zaliczenie na ocenę
Ćwiczenia - Zaliczenie na ocenę |
|
| Pełny opis: |
(tylko po angielsku) The course is intended for students that want to learn methods for exploring data structure (Exploratory Factor Analysis – EFA and PCA; Multidimensional Scaling and Clustering algorithms). The focus will be both on applying it in own research and/or to evaluate the work of others. Covered material will include: Data structure: - PCA and EFA logic and utility - EFA – models, assumptions and diagnostics (tests and plots) - extraction and rotation and methods for establishing number of factors / components Clustering: - Clustering – methods and utilities for social sciences - Different algorithms, similarity and dissimilarity measures, establishing number of clusters - validity of clusters, stability of cluster solutions - practical approaches to clustering Scaling: - purpose of multidimensional scaling (MDS) - proximities and preferences as data - MDS models - goodness of fit Specific topics and amount of covered material will depend in part on the interests of the students and class progress. For instance, if needed, we may want to cover the confirmatory factor analysis. |
|
| Literatura: |
(tylko po angielsku) Basic Literature (may be subject to change): Aldenderfer, Mark S. and Roger K. Blashfield (1984). Cluster analysis. Quantitative Applications in the Social Sciences Series No. 44. Thousand Oaks, CA: Sage Publications Kruskal, Joseph B. & Wish, Myron (1978). Multidimensional scaling. Sage University Paper Series on Quantitaive Applications in the Social Sciences. Beverly Hills, CA: Sage Publications. Dunteman, George H. (1989). Principal components analysis. Quantitative Applications in the Social Sciences Series, No. 69. Thousand Oaks, CA: Sage Publications Kim, Jae-On and Charles W. Mueller (1978a). Introduction to factor analysis: What it is and how to do it. Quantitative Applications in the Social Sciences Series, No. 13. Thousand Oaks, CA: Sage Publications Kim, Jae-On and Charles W. Mueller (1978b). Factor Analysis: Statistical methods and practical issues, Quantitative Applications in the Social Sciences Series, No. 14, Thousand Oaks, CA: Sage Publications Note: Additional literature may be updated on the first class and/or added to the list. |
|
Zajęcia w cyklu "Semestr zimowy 2024/25" (zakończony)
| Okres: | 2024-10-01 - 2025-01-26 |
PN WT ŚR CZ CW
PT |
| Typ zajęć: |
Ćwiczenia, 30 godzin
|
|
| Koordynatorzy: | Mikołaj Winiewski | |
| Prowadzący grup: | Maciej Bieńkowski, Mikołaj Winiewski | |
| Lista studentów: | (nie masz dostępu) | |
| Zaliczenie: |
Przedmiot -
Zaliczenie na ocenę
Ćwiczenia - Zaliczenie na ocenę |
|
| Pełny opis: |
(tylko po angielsku) The course is intended for students that want to learn methods for exploring data structure (Exploratory Factor Analysis – EFA and PCA; Multidimensional Scaling and Clustering algorithms). The focus will be both on applying it in own research and/or to evaluate the work of others. Covered material will include: Data structure: - PCA and EFA logic and utility - EFA – models, assumptions and diagnostics (tests and plots) - extraction and rotation and methods for establishing number of factors / components Clustering: - Clustering – methods and utilities for social sciences - Different algorithms, similarity and dissimilarity measures, establishing number of clusters - validity of clusters, stability of cluster solutions - practical approaches to clustering Scaling: - purpose of multidimensional scaling (MDS) - proximities and preferences as data - MDS models - goodness of fit Specific topics and amount of covered material will depend in part on the interests of the students and class progress. For instance, if needed, we may want to cover the confirmatory factor analysis. |
|
| Literatura: |
(tylko po angielsku) Basic Literature (may be subject to change): Aldenderfer, Mark S. and Roger K. Blashfield (1984). Cluster analysis. Quantitative Applications in the Social Sciences Series No. 44. Thousand Oaks, CA: Sage Publications Kruskal, Joseph B. & Wish, Myron (1978). Multidimensional scaling. Sage University Paper Series on Quantitaive Applications in the Social Sciences. Beverly Hills, CA: Sage Publications. Dunteman, George H. (1989). Principal components analysis. Quantitative Applications in the Social Sciences Series, No. 69. Thousand Oaks, CA: Sage Publications Kim, Jae-On and Charles W. Mueller (1978a). Introduction to factor analysis: What it is and how to do it. Quantitative Applications in the Social Sciences Series, No. 13. Thousand Oaks, CA: Sage Publications Kim, Jae-On and Charles W. Mueller (1978b). Factor Analysis: Statistical methods and practical issues, Quantitative Applications in the Social Sciences Series, No. 14, Thousand Oaks, CA: Sage Publications Note: Additional literature may be updated on the first class and/or added to the list. |
|
Właścicielem praw autorskich jest Uniwersytet Warszawski.
