UGC NET Questions (Paper – 1)

Statements A, B, C and D correctly distinguish parametric and non-parametric tests. Parametric tests rest on stronger distributional assumptions and are suited to interval or ratio data, while non-parametric tests are more flexible and can be used for ordinal data or when assumptions are violated. Statement E is false because the appropriateness and accuracy of a test depend on how well its assumptions fit the data; non-parametric tests are not automatically superior. Thus, the set containing A, B, C and D is the only correct combination.

Option A:
Option A includes A, B and C but omits D, failing to note that non-parametric procedures are particularly useful when parametric assumptions do not hold or when dealing with ordinal data. Without D, the practical role of non-parametric tests is understated.

Option B:
Option B lists B, C and D but omits A, so it does not explicitly state that parametric methods assume particular distributions such as normality. This omission weakens the conceptual contrast between the two types of tests.

Option C:
Option C contains A, C and D but leaves out B, thereby not acknowledging that non-parametric tests make fewer assumptions about population form. Since B is a central descriptive point, its absence makes this combination incomplete.

Option D:
Option D is correct because it combines all four accurate statements and excludes E, which exaggerates the superiority of non-parametric methods. It presents a balanced view of when each class of tests is appropriate.

A ranking scale requires respondents to place items in a preferred order, such as first, second, third and so on. This produces ordinal data because the order is meaningful but the exact differences between ranks are not known. Ranking scales are useful when researchers want relative preferences among several alternatives. Because the stem emphasises arranging items in order of preference, a ranking scale is the correct answer.

Option A:
Nominal scales only classify items into categories without any inherent order, such as types of institution or subject specialisation. They do not capture preference ranking or ordering among categories. Therefore, a nominal scale does not correspond to the procedure described in the question.

Option B:
Rating scales ask respondents to indicate the degree of agreement, satisfaction or intensity on a continuum, such as from “strongly agree” to “strongly disagree.” Ratings express intensity rather than an ordered list of multiple items relative to each other. Hence, rating is not the best completion for the stem.

Option C:
A ranking scale records positions of items like most preferred to least preferred, allowing the researcher to see relative standing among options. This is different from measuring equal intervals or absolute amounts. Since the question describes ordering items by preference, ranking scale correctly captures the intended idea.

Option D:
An interval scale assumes equal distances between successive points and enables meaningful addition and subtraction, such as in temperature measurement. It is not defined by asking respondents to order a list of options. Therefore, interval is not the appropriate term here.

The Likert scale is a widely used attitude measurement technique in which respondents indicate their degree of agreement or disagreement with statements, typically on a five- or seven-point ordered scale. Responses such as “strongly agree,” “agree,” “neutral,” “disagree” and “strongly disagree” are assigned numerical values that can be summed to yield an overall attitude score. Although the data are ordinal, researchers often treat them as approximately interval for many statistical analyses. Because the stem clearly describes an ordered agreement continuum used to measure attitudes, this is known as a Likert scale.

Option A:
Semantic differential scales present bipolar adjective pairs (such as good–bad, strong–weak) and ask respondents to indicate their position between the two on a series of semantic dimensions. While they also use ordered response categories, they focus on underlying connotative meanings rather than levels of agreement with statements. Thus, semantic differential is not the best match for the scale described in the stem.

Option B:
Guttman scales, also called cumulative scales, arrange items so that agreement with a stronger statement implies agreement with all weaker statements in the set. They require a specific hierarchical structure among items, which is not implied by the simple agreement continuum in the question. Therefore, Guttman is not the correct answer.

Option C:
Thurstone scales rely on expert judges to assign scale values to attitude statements, which are then presented to respondents who indicate which statements they agree with. The scoring procedure differs significantly from the straightforward ordered agreement options mentioned in the stem. As such, Thurstone scaling is not the appropriate label here.

Option D:
Likert scales are favoured for their simplicity in construction and administration, requiring only statements and ordered response alternatives. Because the stem focuses on measuring attitudes via agreement levels on a response continuum, the term Likert scale accurately completes the statement.