To reduce data complexity (e.g., Factor Analysis, PCA)
To identify patterns and groups (e.g., Cluster Analysis)
To predict outcomes using multiple predictors (e.g., Regression, Discriminant Analysis)
To test hypotheses involving multiple dependent/independent variables (e.g., MANOVA, SEM)
To visualize associations in multidimensional space (e.g., Correspondence Analysis, Canonical Correlation
ü Research Methods – An Overview, Questionnaire, Data Types, Objectives, Variable Identification, Measurement, and Tests
ü Exploratory Factor Analysis
ü Reliability
ü Multiple Regression Analysis
ü Cluster Analysis
ü Multiple Discriminant Analysis
ü Multiple Analysis of Variance (MANOVA)
ü Canonical Correlation Analysis
ü Correspondence Analysis and
ü Neural Network Analysis (NNA)
Register: https://forms.gle/6WTAfEuNbFLUSZJP6