Multivariate Analysis 2600-ABdz1AWkf
1. Introduction to Multidimensional Data Analysis
• Characteristics of data sets, high-dimensional problems, standardization of variables.
2. Multiple Regression and MANOVA
• Applications in business research (e.g., factors influencing customer satisfaction).
3. Principal Component Analysis (PCA)
• Dimensionality reduction, visualization, applications in market segmentation.
4. Factor Analysis
• Latent factors, interpretation, applications in preference research.
5. Clustering
• Hierarchical and non-hierarchical methods, customer segmentation.
6. Discriminant Analysis
• Object classification, comparison with machine learning methods.
7. Correspondence Analysis and Exploratory Methods
• Applications in consumer preference analysis and marketing research.
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Term 2025Z:
1. Introduction to Multidimensional Data Analysis |
Type of course
Course coordinators
Learning outcomes
Upon completion of the course, the student:
In terms of knowledge:
• Knows basic multivariate analysis methods, their assumptions, and limitations (K_W01),
• Understands the application of methods in business and marketing analyses (K_W05).
In terms of skills:
• Is able to select the appropriate tool to solve an analytical problem (K_U01),
• Performs multivariate analyses using computer software (K_U03),
• Interprets and presents analysis results in a business context (K_U09).
In terms of social skills:
• Understands the importance of reliable data analysis for decision-making processes,
• Is able to work in a team on an analytical project.
Assessment criteria
Final Test
Number of points/grade
Passed by more than 50% of points
Practical placement
Internship is not required to complete the course.
Bibliography
1.Aczel A.D. (2000). Statystyka w zarządzaniu. PWN..
2.Gatnar, E., Walesiak, M. (red.) (2012). Statystyczne analiza danych z wykorzystaniem programu R. PWN.
3.Panek T., Zwierzchowski J, (2013). Statystyczne metody wielowymiarowej analizy porównawczej: teoria i zastosowania. Oficyna Wydawnicza SGH, Warszawa
4.Stanisz, A. (2007). Przystępny kurs statystyki z zastosowaniem Statistica PL na przykładach z medycyny. Tom 3: Analizy wielowymiarowe. StatSoft Polska, Kraków.
5.Anderson, T.W. (2003). An Introduction to Multivariate Statistical Analysis. Wiley.
6.Johnson, R.A., Wichern, D.W. (2007). Applied Multivariate Statistical Analysis. Pearson.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: