Factor Analysis
A statistical technique that identifies underlying dimensions, or factors, explaining the pattern of correlations among a set of observed variables.
Factor analysis examines the correlations among many observed variables, often questionnaire items, and explains them with a smaller number of unobserved factors. Exploratory factor analysis discovers how many factors underlie the data and which items load on each; confirmatory factor analysis tests whether a hypothesized structure fits. Loadings show how strongly each item relates to a factor, and rotation makes the pattern easier to interpret.
The method needs an adequate sample, suitable correlations among items, and judgment calls about how many factors to retain, all of which should be reported transparently.
For a thesis, factor analysis is most useful when developing or adapting a questionnaire: it shows whether the items group into the intended subscales before you compute scale scores and Cronbach's alpha. Reporting the procedure openly strengthens the validity argument in your methodology chapter.
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