Born in Berlin in 1916 to Jewish mother and Catholic father. Moved to London in 1934 after parents divorced. Earned Ph.D. in psychology from University College London in 1940
SEM combines factor analysis and regression/path analysis for behavioral sciences. Models are visualized using path diagrams with boxes and circles. Latent factors represent theoretical constructs, observed variables show relationships
Statistical analysis collects, organizes, and interprets data to identify trends and relationships. It transforms data into actionable insights for various business functions
EFA identifies underlying structure of large set of variables. Used when no prior hypothesis about factors exists. Based on common factor model with manifest variables and factors. Should be used before confirmatory factor analysis
Factor analysis helps explore variable structure and reduce data dimensionality. Data should be clean and free of missing values and outliers. Bartlett's test and Kaiser-Meyer-Olkin measure should be conducted
Multivariate analysis examines multiple variables simultaneously. Technological advances enable rapid analysis of complex data. Businesses need effective knowledge creation and management