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| Analiza wariancji (ANOVA)× | Factor Analysis× | |
|---|---|---|
| Dziedzina | Statystyka w badaniach | Statystyka w badaniach |
| Rodzina | Process / pipeline | Process / pipeline |
| Rok powstania≠ | 1925 | 1931 |
| Twórca≠ | Ronald A. Fisher | Louis Leon Thurstone |
| Typ | Method | Method |
| Źródło pierwotne≠ | Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver and Boyd. link ↗ | Thurstone, L. L. (1947). Multiple Factor Analysis. University of Chicago Press. DOI ↗ |
| Inne nazwy≠ | ANOVA, F-test | EFA, CFA, latent variable modeling |
| Pokrewne≠ | 4 | 3 |
| Podsumowanie≠ | ANOVA is a parametric statistical method developed by Ronald A. Fisher in 1925 that tests whether means differ significantly across three or more independent groups. By partitioning total variance into between-group and within-group components, ANOVA determines whether observed differences are likely due to treatment effects or random variation, making it fundamental to comparative research across medicine, psychology, agriculture, and engineering. | Factor analysis is a statistical technique for identifying latent (unobserved) dimensions underlying observed variables, developed by Louis Leon Thurstone in the 1930s and formalized by Jöreskog (1969). Exploratory factor analysis (EFA) discovers unknown factor structure from data; confirmatory factor analysis (CFA) tests hypothesized relationships between observed and latent variables. Essential in psychometrics (test development), organizational research (measuring constructs like leadership style), and biomedicine (identifying disease subtypes), factor analysis reduces dimensionality while revealing conceptual organization in multivariate data. |
| ScholarGateZbiór danych ↗ |
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