Regression prediction purpose – UGC NET Question

Regression analysis models the relationship between a dependent variable and one or more independent variables to predict or explain outcomes. In simple regression, a straight line is fitted to data points, whereas multiple regression uses several predictors. Regression coefficients indicate the direction and magnitude of each predictor’s effect. Therefore, the technique used to predict a dependent variable from predictors is correctly termed regression analysis.

Option A:
Correlation measures the strength and direction of association between variables but does not provide an explicit predictive equation specifying expected values of the dependent variable given specific independent variable scores.

Option B:
Regression offers both prediction and partial explanation by quantifying how changes in predictor variables are associated with changes in the outcome, holding other variables constant. This predictive focus corresponds precisely to the stem, making this option correct.

Option C:
Factor analysis identifies underlying latent dimensions that account for correlations among observed variables and is not primarily used for predicting one variable from others.

Option D:
Cluster analysis groups cases into relatively homogeneous clusters based on similarity but does not predict a single dependent variable from predictors.