UGC NET Questions (Paper – 1)

In this question statements A, B and C appropriately describe the concepts of population, sample and probability sampling. Statement A is true because the population refers to the total set of units about which the researcher wants to generalise. Statement B is correct in defining a sample as a subset of that population, and statement C accurately reflects that in probability sampling every element has a known non-zero chance of selection. Statements D and E are wrong: D incorrectly labels convenience sampling as a rigorous probability technique, and E wrongly suggests that a large sample size alone guarantees representativeness regardless of sampling method, so the wrong statements are exactly D and E.

Option A:
Option A brings together statements D and E, both of which misrepresent sampling concepts. It recognises that convenience sampling is a non-probability method and that large sample size without appropriate sampling design cannot ensure representativeness. Because it neither omits any wrong statements nor includes any correct ones, this combination is the correct answer.

Option B:
Option B treats statement D as the only wrong statement and thus ignores the error contained in statement E. While it is true that calling convenience sampling a rigorous probability method is incorrect, it is equally incorrect to claim that sample size alone guarantees representativeness. Since this option fails to capture all the wrong statements, it cannot be accepted.

Option C:
Option C identifies only statement E as wrong and overlooks statement D. It is right to challenge E because representativeness depends on the sampling technique and frame, not just on the size. However, by failing to mark D as wrong, this option does not fully answer the question.

Option D:
Option D erroneously includes statement C among the wrong statements. Statement C correctly defines probability sampling as giving every element a known non-zero chance of selection. By classifying a correct statement as incorrect, this combination becomes logically inconsistent and therefore cannot be the correct answer.

In research, the population refers to the complete set of individuals or elements that share specified characteristics and about which the researcher wants to draw conclusions. The sample is selected from this population to provide data that, under proper sampling, can be generalised back to it. Defining the population clearly is a critical step in planning a study. Thus, the group described in the stem is called the population.

Option A:
A sample consists of a subset of the population chosen for actual observation or measurement. While findings are based on the sample, they are intended to represent the population, which is broader than the sample itself. Therefore, sample is not the correct completion.

Option B:
The population is sometimes referred to as the universe in statistical writing, but the term population is more commonly used in research methodology. It emphasises the target group for which inferences are intended. This matches the stem’s focus on generalisation, so this option is correct.

Option C:
A parameter is a numerical characteristic of a population, such as the true mean, which is estimated from sample statistics. It is not the group itself.

Option D:
A frame, or sampling frame, is the list of population members from which the sample is drawn. Although related to sampling, it is distinct from the entire group described as the population.

Statements A, B, C, D and E together summarise basic terminology in sampling theory. A is true because the population is the full set of units to which the researcher wants to generalise, and B correctly defines a statistic as a value computed from a sample. Statement C accurately describes a parameter as a population characteristic, while D explains that parameters are typically unknown and estimated using statistics. E is also correct in noting that a census attempts to cover every unit, whereas F is false because measurement error can still occur even in a complete enumeration.

Option A:
Option A omits statement E, thereby failing to mention the important notion of a census study. Since E is a correct statement about covering every unit of the population, leaving it out means the option does not include all correct statements. Hence, it is incomplete.

Option B:
Option B includes F, which wrongly suggests that measurement error disappears once a census is conducted. Even when every unit is measured, instruments and respondents can still introduce error. Because Option B mixes a false statement with true ones, it cannot be the correct answer.

Option C:
Option C is correct because it lists A, B, C, D and E, all of which align with standard definitions in population and sampling concepts. It deliberately excludes F, which underestimates the possibility of measurement error. Thus this combination contains all and only the true statements.

Option D:
Option D drops statement A, ignoring the central definition of population, and includes F, which is false. By omitting a key true statement and adding an incorrect one, this combination misrepresents the basic concepts and is therefore invalid.

A sample is the smaller group of units selected from a larger population for the purpose of observation and measurement. It is chosen in such a way that it can provide information about the characteristics of the whole population. Researchers rely on samples because studying every member of the population is often impractical or impossible. Thus, the subset of the population from which data are actually collected is correctly called the sample.

Option A:
The sample serves as the empirical basis for estimating population parameters and testing hypotheses about the wider group. When selected appropriately, it can yield findings that generalise with known margins of error. This makes sample the most accurate completion of the stem.

Option B:
Universe or population refers to the entire collection of units about which the researcher wishes to draw conclusions. It is not limited to those units that are observed directly. Therefore, universe is not the correct answer for the subset actually studied.

Option C:
A parameter is a numerical value that describes some characteristic of a population, such as the true mean or proportion. It is not the group of units themselves but rather a summary descriptor. Hence, parameter cannot complete the stem correctly.

Option D:
A statistic is a numerical value computed from sample data used to estimate parameters, such as the sample mean. It is derived from the sample but is not the subset of units that is selected and measured. Therefore, statistic is not the appropriate term here.

The population is the complete set of individuals, objects or events that meet specified criteria and about which the researcher wants to make inferences. Samples are drawn from this larger group to make the study feasible. Correctly defining the population is essential for valid generalisation of findings. Thus, the group described in the stem is known as the population.

Option A:
A sample is only a subset of the population selected for actual observation or measurement. While conclusions are often generalised from the sample to the population, the sample itself is not the entire group of interest. Hence, sample is not the best completion.

Option B:
A parameter is a numerical characteristic of a population, such as a population mean, and summarises information about it. It is not the group itself but a descriptor of it, so parameter does not fit the stem.

Option C:
Option C, population, emphasises that the researcher’s ultimate conclusions and generalisations are targeted at this larger universe, not just at the participants who were studied directly. This aligns precisely with the description given.

Option D:
A statistic is a numerical value calculated from sample data, such as a sample mean, and is used to estimate the corresponding parameter. It is not the entire group of elements, so statistic is not appropriate here.