UGC NET Questions (Paper – 1)

A continuous variable can take on any value within a given range and be subdivided into finer units. Weight is continuous because it can, in principle, be recorded with decimal precision such as 55.2 or 55.23 kilograms, making it suitable for many statistical techniques that assume continuity.

Option A:
This option refers to the number of students, which is a discrete variable because it can only take whole number values; you cannot have 30.5 students.

Option B:
This option correctly identifies weight measured on a metric scale as continuous; it can vary in very small increments and be represented by real numbers.

Option C:
This option describes type of school management, which is a categorical (nominal) variable rather than a continuous one.

Option D:
This option refers to gender categories such as male or female, which are also nominal and not continuous numerical measures.

Parametric tests, such as t tests and ANOVA, rely on certain assumptions about the population distribution and measurement scale. Typically, they assume that the underlying population is approximately normal and that the data are measured on interval or ratio scales. When these assumptions are reasonably met, parametric tests are powerful tools for detecting differences and relationships.

Option A:
Option A describes conditions more suitable for nonparametric tests, which handle nominal data and skewed distributions better. Parametric procedures would often be invalid in such cases.

Option B:
Option B correctly states the usual requirements for parametric testing, including approximate normality and higher level measurement scales. Under these conditions, parametric tests provide efficient and interpretable inferences.

Option C:
Option C claims that no assumptions can be made about the population distribution, which contradicts the very nature of parametric methods. Their validity depends on assumed distributions and other conditions like homogeneity of variance.

Option D:
Option D focuses on extremely small samples and unequal categories, again a context where nonparametric tests or exact methods might be preferred.