UGC NET Questions (Paper – 1)

Statements A, B and C correctly distinguish the main interview types: structured (fixed questions), unstructured (high flexibility) and semi-structured (a mix of standardised questions and probes). Statement D is false because structured interviews are often used in quantitative surveys, and E is false because unstructured interviews are well known for yielding rich narratives. Therefore, the option including A, B and C alone is correct.

Option A:
Option A is correct because it summarises the three key interview formats without endorsing the restrictive or inaccurate claims in D and E. It highlights the continuum from structure to flexibility.

Option B:
Option B is incorrect because it includes D, which wrongly limits structured interviews to qualitative work, ignoring their common use in survey research. This erroneous statement makes the combination invalid.

Option C:
Option C is wrong because it accepts E, which denies the rich narrative potential of unstructured interviews, and omits A, thereby not explicitly recognising the fixed nature of structured interviews.

Option D:
Option D includes D and thus repeats the mistake that structured interviews cannot support quantitative analysis, even though they often generate standardised data suited to statistical treatment.

Statements A, B, C and E correctly describe how computers and specialised software support research. They help with data management, statistical analysis, citation organisation and qualitative coding and visualisation. Statement D is false because the use of software does not eliminate the need to understand statistics; researchers must still select appropriate tests, interpret outputs and recognise limitations. Thus, the combination including A, B, C and E is correct.

Option A:
Option A is incomplete as it omits E, overlooking the important role of qualitative data analysis software in handling textual or multimedia materials. Without E, the option gives a partial picture focused mainly on quantitative and reference tasks.

Option B:
Option B contains B, C and E but leaves out A, failing to note that basic data storage and cleaning are fundamental computer-assisted tasks in research. This omission makes the description of computer use incomplete.

Option C:
Option C includes A, C and E but omits B, thereby ignoring the central role of statistical software packages, which are key tools in empirical research. As such, this option does not cover the full range of computer applications.

Option D:
Option D is correct because it groups all the true statements together and excludes D, which wrongly suggests that conceptual understanding of statistics is unnecessary. It recognises computers as powerful aids, not substitutes for methodological competence.

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.

The case study method involves intensive, holistic examination of a single case such as a person, class, school or programme. Data are collected from multiple sources, including documents, observations and interviews, to build a rich, contextualised picture. This method is especially useful when the researcher seeks to understand complex processes and unique features rather than to generalise statistically. Therefore, the in-depth investigation described in the stem is correctly termed a case study.

Option A:
Survey methods collect data from many respondents, usually at one point in time, to describe patterns or relationships, not to examine one case in depth. They lack the detailed, contextual focus highlighted in the stem.

Option B:
Experimental methods manipulate variables and use control groups to test hypotheses, which typically involve more than one case and aim at causal generalisation rather than detailed description of a single unit. Thus, they do not fit the stem.

Option C:
A case study uses triangulation of multiple data sources and perspectives to build an in-depth narrative or analysis of the case. It often reveals insights about processes, meanings and interactions that might be missed in broader surveys. These features correspond exactly to the description given, making this option correct.

Option D:
Correlational methods focus on measuring the strength and direction of relationships between variables across many cases and do not centre on intensive study of a single individual or institution.

The review of related literature is a systematic examination, summary and critique of past research and theoretical writings on the topic. It helps identify what is already known, where the gaps or inconsistencies lie and how the present study can contribute. By organising and evaluating earlier work, the researcher situates the new study within the broader knowledge base. Because the stem mentions a critical summary and synthesis of existing research, review of related literature is the most accurate term.

Option A:
Research design describes the overall strategy and structure for conducting the study, including methods of data collection and analysis. It does not primarily focus on summarising and critiquing previous research findings. Therefore, research design does not match the function described in the stem.

Option B:
A research synopsis is usually a concise proposal or outline of a planned study submitted for approval, covering the problem, objectives, methods and expected outcomes. While it may briefly mention some literature, it is not itself the critical survey of prior studies that the question refers to. Thus, research synopsis is not appropriate here.

Option C:
The review of related literature organises prior studies thematically or conceptually and highlights areas that require further investigation. It guides the formulation of research questions, hypotheses and design choices. These roles align directly with the stem’s description of a critical summary and synthesis of existing research, confirming it as the correct answer.

Option D:
Data interpretation is the stage at which the researcher explains the meaning of the analysed data from the current study, not a summary of previous work. It deals with the new findings rather than with the existing body of research. Consequently, data interpretation is not the correct completion.

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.

Probability sampling is characterised by the use of random selection mechanisms that give each element in the population a known, non-zero chance of being included in the sample. This property allows researchers to estimate sampling error and use statistical inference to generalise from the sample to the population. Techniques such as simple random, stratified and systematic sampling fall under this category. Therefore, the sampling procedure described in the stem is correctly called probability sampling.

Option A:
Non-probability sampling does not give every member of the population a known chance of selection, often relying on convenience, judgement or voluntary participation. As a result, sampling error cannot be strictly quantified, and generalisations are more tentative. Hence, non-probability sampling is not the correct completion.

Option B:
Convenience sampling selects whoever is easiest to reach, without any randomisation or known probabilities of selection. It is prone to bias and lacks the formal properties required for probability-based inference, so convenience sampling does not match the stem.

Option C:
In probability sampling, each element’s inclusion likelihood can theoretically be specified, which underpins many statistical tests and confidence interval calculations. This feature aligns exactly with the requirement stated in the question.

Option D:
Judgement sampling, also known as purposive sampling, involves selecting units based on the researcher’s subjective judgement about their relevance or typicality and thus does not provide a known non-zero probability of selection. Therefore, judgement sampling is not appropriate here.

Statements A, B, D and E correctly express key ethical principles: ethics committees protect participants, informed consent demands adequate information, participants must have the right to withdraw and vulnerable groups require special safeguards. Statement C is false because coercing participation violates autonomy and ethical guidelines, regardless of concerns about bias. Thus, the combination that includes A, B, D and E and excludes C is correct.

Option A:
Option A is incomplete because it omits E, failing to acknowledge the particular responsibilities involved in working with vulnerable populations such as children or persons with disabilities.

Option B:
Option B is incorrect because it leaves out A, not explicitly describing the formal role of ethics committees in reviewing and monitoring research proposals.

Option C:
Option C is incomplete as it omits B, and therefore does not clearly emphasise the need for informed consent information as part of ethical practice.

Option D:
Option D is correct because it gathers all true statements about ethical review and consent, while rejecting C, which endorses coercion. It reflects established international norms for research with human participants.

Statements A, B, C and E together describe the standard components of a research proposal. A proposal normally states the problem and background, sets out objectives or hypotheses, explains sampling and procedures in the methodology and includes a targeted review of literature to justify the work. Statement D is false because ethical issues are especially important when human participants are involved and should be explicitly addressed. Thus, the only correct combination is the one that includes A, B, C and E and excludes D.

Option A:
Option A is incomplete because it omits statement E, which recognises the important role of literature review in situating the proposed study. Without E, the proposal appears disconnected from previous work, so this combination does not cover all the correct elements.

Option B:
Option B includes B, C and E but leaves out A, thereby failing to mention the need for a clear problem statement and background. Since a well-defined problem is a core feature of any proposal, the omission of A prevents this option from being correct.

Option C:
Option C contains A, C and E but omits B, ignoring the statement that objectives, questions or hypotheses should be outlined. Without B, the proposal lacks clearly articulated aims, so the combination is incomplete.

Option D:
Option D is correct because it assembles all true statements and leaves out D, which wrongly implies that ethical considerations can be ignored in proposals involving human participants. It aligns with standard expectations from funding agencies and ethics committees.

Statements A, B, C and D identify key error sources in surveys, and F points to one mitigation strategy. A is true because coverage error arises when parts of the population are missing from the frame, and B correctly defines non-response error. C is accurate in linking measurement error to poor wording or misunderstanding, while D recognises that different modes of administration can affect responses. F is also true since repeated contacts and follow-ups can reduce non-response, whereas E is false because social desirability bias can distort answers and undermine validity.

Option A:
Option A omits statement F, thereby failing to recognise a practical method for reducing non-response error. Although A, B, C and D are correct, the lack of F makes the option less complete in terms of both diagnosis and remedy.

Option B:
Option B leaves out statement A, ignoring the important concept of coverage error, which can prevent some population members from being sampled at all. Without A, the picture of survey validity threats is incomplete, so this option is not acceptable.

Option C:
Option C excludes statement B, neglecting the impact of non-response error on survey conclusions. Even though it includes A, C, D and F, missing B means the combination does not cover all the major threats listed.

Option D:
Option D is correct because it includes A, B, C, D and F, summarising coverage, non-response, measurement and mode effects as well as follow-up strategies. It excludes E, which wrongly claims that social desirability bias has no effect on validity. Therefore, this combination contains all and only the true statements.

A ratio scale possesses all the properties of an interval scale—equal units and meaningful differences—but also includes a true zero point that indicates the absence of the measured attribute. This allows researchers to say that one score is twice or half another in a meaningful way, as in weight or height. Because of these features, ratio scales support the full range of mathematical operations. Thus, the scale described in the stem is correctly called the ratio scale.

Option A:
Ordinal scales allow ranking of cases but do not guarantee equal intervals between ranks, nor do they have a true zero. Numbers indicate order only, not the magnitude of differences, so ordinal scale does not match the properties described in the question.

Option B:
Nominal scales provide categorical labels without quantitative meaning or order and have no concept of interval or zero magnitude. They cannot support ratio statements like “twice as much.” Hence, nominal scale is not appropriate here.

Option C:
Interval scales do have equal units, enabling meaningful comparison of differences, but they lack a true zero point, as seen in Celsius temperature. This absence prevents meaningful ratio interpretations, so interval scale falls short of the description given in the stem.

Option D:
Ratio scales, by including a natural zero, make statements like “this object weighs twice as much as that one” legitimate, which is exactly the property highlighted in the question. This confirms ratio as the correct answer.

Standard deviation quantifies the spread of scores around the mean by taking the square root of the average of squared deviations. A larger standard deviation indicates that scores are more widely dispersed, while a smaller one shows they cluster closely around the mean. It is widely used because it relates directly to variance and plays a central role in many statistical procedures. Therefore, the measure described in the stem is correctly called the standard deviation.

Option A:
Standard deviation provides a more informative picture of variability than the range because it considers all data points, not just extremes. It is also compatible with normal distribution theory and confidence intervals, making it a fundamental descriptive statistic. These properties align with the stem’s focus on average deviation from the mean, so this option is correct.

Option B:
The mean is a measure of central tendency, representing the average score, and does not describe how far scores typically lie from that average.

Option C:
The mode is the most frequently occurring value in a distribution and gives no information about overall dispersion.

Option D:
The range is the difference between the highest and lowest scores and is sensitive only to extreme values, not to the overall spread, so it does not match the stem.

Informed consent is an ethical procedure in which researchers clearly explain the purpose, procedures, potential risks and benefits of a study to prospective participants and ensure that participation is voluntary. Participants are given the opportunity to ask questions and to refuse or withdraw without penalty. This respects their autonomy and right to make an informed choice. Because the stem highlights providing information and obtaining voluntary agreement, informed consent is the correct term.

Option A:
Informed consent requires that information be presented in understandable language and that no coercion or undue influence is used. Signed consent forms or documented verbal consent often serve as evidence that this ethical requirement has been met. These aspects closely match the situation described in the stem.

Option B:
Debriefing is an ethical step taken after participation, especially in studies involving deception, where researchers reveal the true purpose of the study and address any misconceptions. It occurs after data collection rather than before participation, so it does not fit the description in the question.

Option C:
Anonymity means that participants’ identities are not attached to their responses so that even the researcher cannot link specific data to individuals. While it protects privacy, it is not the process of informing participants about the study beforehand, so anonymity is not the correct answer.

Option D:
Confidentiality involves safeguarding participants’ data so that their identities are not disclosed to unauthorised persons. It is part of ethical practice but refers to data handling rather than to the initial information and voluntary agreement process described in the stem.

Statements A, B, C and D accurately distinguish between positivist and interpretivist paradigms. Positivism stresses objective measurement and is often linked with experiments and surveys, while interpretivism focuses on meanings and experiences using methods like observation and interviews. Statement E is false because interpretivism rejects the notion of a single fixed reality independent of the researcher; it emphasises multiple, constructed realities. 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 mention the qualitative methods commonly used in interpretivist research. Without D, the methodological side of interpretivism is underrepresented.

Option B:
Option B is incorrect because it adds E, which contradicts interpretivist assumptions about multiple realities and researcher involvement. Including E mischaracterises interpretivism as having a strictly objectivist stance.

Option C:
Option C is wrong because it includes only B, C and D, omitting A and thus not stating clearly that positivism emphasises objective measurement and quantification. This weakens the contrast between the two paradigms.

Option D:
Option D is correct because it compiles all statements that properly describe the two paradigms and leaves out E, which misstates interpretivist ontology. It reflects both the epistemological and methodological distinctions between positivist and interpretivist approaches.

A quasi-experimental design includes an active intervention or manipulation of an independent variable but does not use full random assignment of participants to groups. As a result, groups may differ on important characteristics before the treatment, making causal inferences more tentative. Such designs are common in real-world settings where randomisation is impractical or unethical. Therefore, the design described in the stem is known as quasi-experimental.

Option A:
Pre-experimental designs often involve one-group pre-test–post-test structures or static group comparisons with very weak control of threats to internal validity. They are usually considered methodologically weaker than quasi-experiments and may lack proper comparison groups. So pre-experimental is not the best completion.

Option B:
Correlational designs examine relationships between variables without manipulation, using naturally occurring variation. They do not involve assigning a treatment or intervention, so they do not match the stem.

Option C:
Ex post facto designs investigate potential causes after outcomes have occurred, without manipulating the independent variable. They are retrospective and non-manipulative, which differs from the active intervention element in quasi-experiments. Hence, ex post facto is not appropriate here.

Option D:
Option D, quasi-experimental design, specifically denotes studies where the researcher manipulates the treatment but uses existing or non-random groups such as intact classes. This fits the question exactly, so it is correct.