UGC NET Questions (Paper – 1)

A Pearson correlation coefficient ranges from −1 to +1 and indicates the strength and direction of a linear relationship. A value of +0.85 is close to +1, suggesting that as one variable increases, the other tends to increase as well in a fairly consistent manner. Although not perfect, this coefficient reflects a strong positive association between the two variables.

Option A:
Option A correctly labels the relationship as strong and positive (and, in the context of Pearson’s r, linear). A coefficient of +0.85 indicates a substantial positive linear association between the variables.

Option B:
Option B claims there is no relationship, which would correspond to a coefficient near zero rather than +0.85. Such a high value clearly signals substantial association.

Option C:
Option C suggests a perfect negative relation, which would correspond to −1.00, not +0.85. Negative correlations indicate that one variable increases while the other decreases.

Option D:
Option D states that the variables are completely independent of each other, which would imply a correlation close to 0, not a large positive value like +0.85.

In this set, statements A, C and D correctly describe aspects of correlational research, while statements B and E are wrong. Statement A is true because correlational studies focus on the degree and direction of relationships between variables without manipulating them. Statement C accurately states that correlation coefficients vary from –1 to +1, and statement D is correct in noting that a coefficient of zero indicates no linear relationship. Statement B is false because correlation, even if high, does not by itself establish causation, and statement E is false since positive correlation means both variables tend to increase or decrease together, whereas a negative correlation describes the pattern where one increases and the other decreases.

Option A:
Option A singles out B as the only wrong statement and ignores E. While B is indeed incorrect because correlation does not imply causation, E is also wrong in describing positive correlation as involving opposite directional change. By failing to treat E as wrong, this option does not capture the full set of incorrect statements.

Option B:
Option B correctly groups B and E as the wrong statements about correlational research. It recognises that interpreting correlation as causation is a conceptual error and that positive correlation has been misdescribed. Since it does not misclassify A, C or D as wrong, this option provides the accurate combination of incorrect statements.

Option C:
Option C marks E as the only wrong statement and overlooks B. Although E is incorrect, B also misleads by equating high correlation with causal influence. Because the option fails to include all wrong statements, it cannot be the right answer.

Option D:
Option D treats A along with B and E as wrong, which is inaccurate. Statement A is actually a correct description of correlational research as investigating relationships between variables. By misclassifying A as wrong and combining it with B and E, this option becomes inconsistent with the basic definition of correlational studies.

Statements A, C and D correctly describe correlational research and the correlation coefficient, while B and E are false. Correlational studies examine relationships without experimental manipulation, positive correlations show variables moving in the same direction and correlation coefficients usually vary between –1 and +1. However, a high correlation does not by itself establish causation, and zero correlation may occur even when measurements are accurate, for example when there is genuinely no linear relationship.

Option A:
Option A is correct because it includes all the true statements and excludes B and E, which confuse correlation with causation and misinterpret zero correlation. It provides a clear picture of what correlational research reveals and what its limits are.

Option B:
Option B wrongly includes B, which claims that high correlation implies causation, a common but serious misunderstanding in research interpretation. Because it accepts this false statement, the whole combination is invalid.

Option C:
Option C includes both B and C, thereby mixing a correct statement about positive correlation with an incorrect causal claim. The presence of B prevents this option from being correct, even though it also contains true statements.

Option D:
Option D adds E, the assertion that zero correlation always signals measurement error, which is false. Zero correlation can reflect a true lack of linear relationship, so this option misinterprets the meaning of r = 0.

Option E combines A and D with E, again bringing in the false idea that zero correlation must be due to error. This contaminates an otherwise partially correct set and makes the option unacceptable.