UGC NET Questions (Paper – 1)

Statements A, B, C and E accurately describe factorial designs, whereas D and F are false. Statement A is true because factorial designs study main effects of multiple independent variables. Statement B correctly notes that interactions between variables can be assessed, and statement C is right about the structure of a 2×3 design. Statement E is also true since each combination of factor levels forms a separate condition, while D is false as factorial designs are common in educational settings and F is false because they are not limited to single-group pre-test–post-test formats.

Option A:
Option A includes all the correct statements (A, B, C and E) and excludes the incorrect ones (D and F). It recognises the capacity of factorial designs to examine main and interaction effects with multiple experimental conditions. Therefore this option is the correct answer.

Option B:
Option B leaves out E, overlooking the fact that each factor-level combination forms its own condition or group. Without E, the description of factorial designs is incomplete and lacks a key structural feature.

Option C:
Option C introduces F along with some correct statements. Since F is false in describing factorial designs as always single-group pre-test–post-test designs, any option containing it cannot be regarded as entirely correct.

Option D:
Option D includes F and omits B, misrepresenting the ability of factorial designs to test interactions and wrongly construing their format. By mixing a false statement with true ones and missing an important correct one, this combination is invalid.

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.

Statements A, B, C and D together describe core characteristics of experimental research. Manipulating independent variables, using control groups, assigning participants randomly and conducting experiments in both laboratory and field contexts are all standard features. Statement E is false because extraneous variables should be controlled or monitored, not ignored, to maintain internal validity. Therefore the correct combination includes A, B, C and D and excludes E.

Option A:
Option A is incomplete because it omits D, thereby failing to acknowledge that experiments need not be confined to laboratories. Field experiments are frequently used in educational and social settings, so leaving out D underrepresents the range of experimental contexts.

Option B:
Option B is correct as it includes all four true statements and omits E, which advises an obviously flawed practice of ignoring extraneous variables. The option reflects the importance of both design and control in experimental work.

Option C:
Option C is incorrect because it includes E, the statement suggesting that extraneous variables may be ignored, which would seriously threaten internal validity. Even though B, C and D are true, the presence of E makes the combination unsuitable.

Option D:
Option D is wrong because it similarly incorporates E and omits B, leaving out the essential comparison role of control groups. Without acknowledging control groups, the design description is incomplete.