UGC NET Questions (Paper – 1)

Factor analysis seeks to reduce a large set of intercorrelated variables to a smaller number of underlying factors that account for common variance. These factors are interpreted as latent constructs such as ability or attitude dimensions. The technique is widely used in test construction and validation to examine the structure of psychological or educational measures. Thus, the method described in the stem is correctly called factor analysis.

Option A:
Discriminant analysis predicts group membership based on predictor variables and is used for classification rather than uncovering latent dimensions underlying correlations.

Option B:
Factor analysis helps researchers determine how many constructs underlie a questionnaire and which items load on each construct, assisting in refining scales and clarifying structure. This emphasis on explaining correlations among variables matches the stem, so this option is correct.

Option C:
Regression analysis models relationships between predictors and an outcome variable but does not primarily aim to reveal latent factors that account for intercorrelations among predictors.

Option D:
Path analysis specifies causal models among observed variables using regression-like equations and directed graphs; it generally assumes variables are already measured constructs, not latent factors to be discovered.