UGC NET Questions (Paper – 1)

A directional hypothesis specifies not only that a relationship or difference exists but also indicates its direction, such as greater than, less than or positive/negative. It leads to one-tailed statistical tests because the region of rejection is placed in one tail of the distribution. This type of hypothesis is usually grounded in prior theory or strong empirical evidence that suggests a particular trend. Hence, a statement predicting that higher motivation will be associated with higher scores is a directional hypothesis.

Option A:
The null hypothesis generally states that there is no difference or no relationship between variables in the population. It does not predict any particular direction of effect and serves as the baseline for statistical testing. Therefore, null hypothesis does not match the directional expectation described in the stem.

Option B:
A non-directional hypothesis asserts that a relationship or difference exists but does not specify whether it is positive or negative, greater or less. It leads to two-tailed tests and is less specific than a directional hypothesis. Since the stem gives a clear upward direction, non-directional hypothesis is not the best fit.

Option C:
A statistical hypothesis is any statement about a population parameter that can be tested using sample data; it may be directional or non-directional. The term is broad and does not explicitly capture the directional nature emphasised in the question. Thus, statistical hypothesis is not the most precise completion.

Option D:
A directional hypothesis, such as “Group A will score higher than Group B,” narrows the predicted outcome, which can increase power if the direction is correct. This explicit specification of direction corresponds exactly to the example given in the stem.

A histogram is a graph that displays the frequency distribution of continuous data using adjoining rectangular bars whose widths correspond to class intervals and whose heights represent frequencies. Because the bars touch, the histogram conveys the idea of continuity in the data. It is widely used to visualise the shape of distributions, such as skewness or modality. Since the stem describes continuous data grouped in class intervals shown as adjacent bars without gaps, histogram is the correct answer.

Option A:
A bar diagram typically represents categorical data with separate bars that have spaces between them, emphasising distinct categories rather than continuity. The presence of gaps distinguishes it from a histogram. Therefore, bar diagram does not match the description provided in the question.

Option B:
An ogive is a cumulative frequency curve that shows how many observations fall below each boundary, helping identify medians and percentiles. It is drawn as a line graph rather than adjoining bars. Hence, ogive is not the appropriate completion for the stem.

Option C:
A frequency polygon depicts frequencies by plotting midpoints of class intervals and joining them with straight lines, forming a polygonal shape. While it also represents grouped data, it does not use adjacent bars and so differs from the graph described in the stem. Consequently, frequency polygon is not the right answer.

Option D:
Histograms allow researchers to quickly see whether data approximate a normal distribution, exhibit skewness or contain outliers. Their defining feature is the touching bars for continuous intervals, exactly as stated in the stem, confirming histogram as the correct term.

In this question statements A, B, D and F correctly describe ethical requirements, while C and E are wrong. Statement A is true because informed participants must know potential risks and benefits. Statement B is correct as voluntary participation includes the right to withdraw, and statement D accurately notes the role of debriefing after partial disclosure. Statement F is true because ethical committees review proposals, whereas C is false since deception is not automatically acceptable and must be carefully justified, and E is false because coercing participation for grades is unethical.

Option A:
Option A focuses only on C as wrong and ignores E. Although C is clearly unethical, E is equally problematic in endorsing coercion of students. By omitting E from the set of wrong statements, this option provides an incomplete answer.

Option B:
Option B correctly identifies both C and E as wrong statements and leaves A, B, D and F as true. It recognises that deception must be tightly controlled and that coercion is unacceptable, especially in teacher–student relationships. Consequently, this combination presents the accurate set of wrong statements and is the correct answer.

Option C:
Option C marks only E as wrong while overlooking C. Even though E is indeed unethical, C also violates basic ethical principles by normalising deception. Failing to include C makes this option incomplete.

Option D:
Option D incorrectly adds D to the wrong set alongside C and E. Statement D is actually correct because debriefing is often required when information has been withheld. Misclassifying D as wrong invalidates this option.

In journal articles, the abstract is a concise paragraph placed at the beginning that summarises the purpose, methodology, main findings and conclusions of the study. It allows potential readers to quickly judge the relevance of the article to their interests. Many databases display only the abstract, making it crucial for visibility. Because the stem describes a short paragraph stating purpose, method and key findings, abstract is the correct term.

Option A:
The abstract distils the entire study into a brief and informative snapshot, often restricted to a specific word limit prescribed by the journal. It provides enough information for readers to decide whether to read the full article without revealing every detail. These features match the description in the question, so abstract correctly completes the sentence.

Option B:
The introduction section situates the research problem, reviews background literature and states objectives or hypotheses. While it may summarise purpose, it does not usually present methods and key findings as briefly as the abstract does. Therefore, introduction is not the best fit for the stem.

Option C:
The discussion section interprets the results, links them to existing literature and explores implications and limitations. It comes after the results and does not serve as a brief overview at the article’s beginning. Thus, discussion is not appropriate here.

Option D:
An appendix contains supplementary material such as detailed tables or instruments, placed at the end of the article if the journal permits it. It does not summarise the purpose, method and findings in a short paragraph. Hence, appendix is not the right completion.

An ordinal scale not only categorises data but also arranges categories in a meaningful order, such as low, medium and high, or first, second and third. However, the distances between these ordered categories are not assumed to be equal, so subtraction and other arithmetic operations on the ranks are not meaningful. This scale allows comparison in terms of “greater than” or “less than” but not precise differences. Because the stem mentions categories that can be ranked but not meaningfully subtracted, it describes an ordinal scale.

Option A:
Ordinal scales appear in many educational settings, such as letter grades (A, B, C) or ranks in a competition. We know that A is better than B and B is better than C, but we cannot say how much better in equal-interval terms. The stem captures exactly this property of ordered but non-interval categories, so ordinal is the correct answer.

Option B:
Nominal scales classify observations into distinct categories without any inherent order, such as gender, blood group or religion. Since nominal data cannot be ranked meaningfully, they do not match the description in the stem, which explicitly mentions the ability to rank categories.

Option C:
Interval scales have equal units between adjacent values, allowing meaningful addition and subtraction, but they lack a true zero point; temperature in Celsius is a standard example. Because the stem stresses that subtraction is not meaningful, an interval scale cannot be the correct option.

Option D:
Ratio scales possess all the properties of interval scales and also have an absolute zero, permitting meaningful multiplication and division; examples include height and weight. With ratio data, subtraction is meaningful, which contradicts the condition stated in the stem. Therefore, ratio scale is not the right completion.

The semantic differential scale measures attitudes by presenting bipolar adjective pairs anchored at the ends of a continuum, and respondents mark their position between them. It captures the connotative meaning of concepts along dimensions like evaluation, potency and activity. This technique yields interval-like data and allows researchers to profile the image of an object or idea. Therefore, a scale using opposite adjectives is correctly called the semantic differential scale.

Option A:
Likert scales ask respondents to indicate degrees of agreement or disagreement with statements and typically use ordered categories like strongly agree to strongly disagree, not bipolar adjective pairs. Thus, they do not match the stem.

Option B:
Thurstone scales use statements previously judged for favourableness and assign scale values; respondents indicate agreement, and their attitude score is computed from these values. They are not based on simple adjective pairs along a line.

Option C:
The semantic differential approach provides visual continua between adjectives, allowing nuanced responses and analysis of multiple dimensions of meaning. Because the stem highlights pairs like “good–bad” and “strong–weak”, this option fits precisely and is correct.

Option D:
Rating-by-ranking is not a standard name for any classical scaling method and does not describe the specific bipolar adjective format of the semantic differential.

Systematic error is a form of measurement error that biases results in a consistent direction, such as always overestimating or underestimating the true value. Unlike random error, it does not average out over repeated measurements and therefore threatens the validity of conclusions. It often arises from faulty instruments, biased procedures or consistent miscalibration. Because the stem describes a consistent tendency to give values higher or lower than the true value, systematic error is the correct term.

Option A:
Random error arises from unpredictable fluctuations in measurement conditions, leading to variations that cancel out over many observations and primarily affect reliability rather than bias. It does not consistently push measurements in one direction, so random error does not match the description in the stem.

Option B:
Sampling error refers to the difference between sample statistics and population parameters that occurs because only a subset of the population is observed. It is related to sample selection rather than to the behaviour of measuring instruments. Therefore, sampling error is not the right completion here.

Option C:
Systematic error is problematic because it can lead to false conclusions even when large samples are used and results appear stable. Researchers must identify and correct sources of systematic bias to preserve validity. These characteristics correspond directly to the stem, confirming systematic error as the appropriate answer.

Option D:
Estimation error is a broader term referring to discrepancies between estimated and true values, which may result from both systematic and random components. The stem, however, specifically focuses on a consistent directional bias, so the more precise term systematic error is preferable.

Basic research focuses on generating new theoretical insights and fundamental principles, often without a direct concern for immediate practical use. It seeks to answer “why” and “how” questions about phenomena to enrich the knowledge base of a discipline. Many later applications and technologies arise from findings of basic research, even though they were not anticipated at the time. Therefore, research aimed at theory development and knowledge expansion is correctly called basic research.

Option A:
Option A, basic research, is typically carried out in universities and research institutes and may appear abstract or highly conceptual. Its value lies in deepening our understanding of underlying laws and relationships, which aligns with the stem’s focus on non-immediate application. Hence, it is the most appropriate choice.

Option B:
Applied research, in contrast, is directed towards solving specific, practical problems in real-world settings. It focuses on immediate utility rather than theoretical generalisation, so it does not match the description given.

Option C:
Action research is a form of applied research in which practitioners study their own practice to bring about immediate improvement. It is context-specific and problem-focused rather than oriented towards general theory-building, so it is not the correct completion.

Option D:
Evaluation research examines the worth or effectiveness of programmes or policies to inform decisions. It is also focused on practical judgments rather than abstract theory construction, so it does not fit the stem.

Assumptions are underlying conditions that the researcher accepts as true for the purposes of the study, even though they are not empirically verified within that investigation. They form the logical foundation on which the design, analysis and interpretation are built. If these assumptions are seriously violated, the conclusions of the study may be undermined. Hence, basic conditions taken as true without proof are called assumptions.

Option A:
Limitations are constraints or weaknesses, such as small sample size or imperfect instruments, that reduce the strength or generalisability of findings. They do not function primarily as logical premises but as acknowledged shortcomings. Therefore, limitations do not match the definition in the stem.

Option B:
Propositions are declarative statements that express relationships between concepts and may be part of a theoretical system. While some propositions might be assumed, the term does not specifically denote the foundational, taken-for-granted conditions of a particular study. Thus, propositions are not the best completion here.

Option C:
Assumptions reflect what the researcher believes to be reasonably true based on prior evidence or accepted practice, such as the validity of a standard test or the sincerity of respondents. These beliefs support the internal coherence of the study without being tested directly. This role aligns precisely with the description given in the question.

Option D:
Hypotheses are tentative predictions that the study seeks to test empirically, rather than starting points taken as given. They may be supported or rejected based on data and are not simply accepted without proof. Consequently, hypotheses are not equivalent to the assumptions described in the stem.

Ex post facto research examines relationships between variables after the events or treatments have already occurred, without the researcher manipulating the independent variable. Groups are formed on the basis of existing characteristics, such as gender or prior experience, and the researcher attempts to infer possible causes of observed differences. Because manipulation and random assignment are not possible, it is classified as a non-experimental design. The stem clearly points to this situation, so ex post facto research is the correct answer.

Option A:
Experimental research actively manipulates one or more independent variables and randomly assigns participants to groups, allowing strong causal inferences. In ex post facto studies, such manipulation is not feasible, so experimental is not an accurate term for the design described.

Option B:
Ex post facto studies try to approximate causal explanations by comparing groups that differ on the independent variable that has already occurred, controlling for some extraneous factors statistically if possible. This aligns with the stem’s key feature: the independent variable cannot be manipulated by the researcher.

Option C:
Action research is a practitioner-led cyclic approach (plan–act–observe–reflect) aimed at improving local practice. It involves intentional interventions by the practitioner, unlike ex post facto designs where the “cause” has already occurred and is not manipulated.

Option D:
Longitudinal research studies the same individuals over time to observe change. While it may involve repeated measures, it is defined by time-based follow-up, not specifically by the “already occurred and cannot be manipulated” feature that defines ex post facto research.

Triangulation involves deliberately combining different approaches, such as interviews, observations and document analysis, or using multiple data sources or researchers to examine the same phenomenon. When findings converge across these diverse angles, confidence in their credibility and validity increases. It reduces the likelihood that results are artefacts of a single method or perspective. Because the stem describes using multiple methods, data sources or investigators to enhance credibility, triangulation is the correct term.

Option A:
Triangulation can be methodological, data, investigator or theory triangulation, each bringing a different kind of diversity to the inquiry. The core idea is convergence of evidence from different directions, which strengthens the overall argument. This is exactly what the stem is highlighting.

Option B:
Randomisation is a procedure for assigning participants to groups or selecting them from populations by chance, thereby controlling bias and enhancing internal validity in experiments. It does not itself refer to combining multiple methods or sources of evidence, so randomisation is not appropriate here.

Option C:
Stratification in sampling means dividing the population into homogeneous subgroups and sampling from each, which helps ensure representation but is not primarily about cross-validating findings through multiple approaches. Therefore, stratification does not match the description in the question.

Option D:
Standardisation refers to using uniform procedures, instructions and scoring rules to ensure consistency across measurements or experimental conditions. While important for reliability, it does not capture the idea of using multiple methods or sources to enhance credibility, so standardisation is not the correct completion.

Causal-comparative research, also called ex post facto, compares groups that already differ on a dependent variable or on a presumed cause to explore possible causal relationships. The researcher does not manipulate the independent variable but attempts to identify factors associated with existing differences. Because groups are not formed randomly, causal inferences are tentative and based on logic rather than strict control. Therefore, the non-experimental design described is correctly termed causal-comparative research.

Option A:
Survey research collects information from respondents using questionnaires or interviews to describe attitudes, behaviours or characteristics; it is not defined by comparing pre-existing groups for causal explanation. Thus, it does not match the stem.

Option B:
Causal-comparative designs use careful selection of groups and statistical controls to reduce alternative explanations, but they cannot fully equate groups the way true experiments with random assignment can. They are useful when manipulation is impossible or unethical. These features align with the description of comparing existing groups to explore causes, so this option is correct.

Option C:
Experimental research introduces treatments and random assignment to groups to test causal hypotheses under controlled conditions, which goes beyond simply observing existing groups. Hence, it is not the best fit here.

Option D:
Ethnographic research focuses on in-depth cultural description through prolonged fieldwork and participant observation rather than formal group comparisons to explore causal factors, so it does not complete the stem.

Here statements A, C, D and F correctly present the role of review of literature, while B and E are wrong. Statement A is true because reviewing existing work prevents unnecessary duplication. Statement C is correct since literature review supports the choice of theoretical framework, and statement D is right that it may suggest tools and designs. Statement F is also true as prior studies help interpret current findings, whereas B is false because review is not restricted to the final stage and E is false because even experts require systematic review to stay updated.

Option A:
Option A labels only B as wrong, but statement E is also incorrect. Although B wrongly postpones literature review to after report writing, E wrongly claims that experts can skip review. Since both B and E misrepresent good practice, this option does not capture the full set of wrong statements.

Option B:
Option B singles out E as wrong but fails to include B. While E is indeed false, B is equally problematic in suggesting an inappropriate timing for the review. Because the option ignores one of the wrong statements, it is incomplete.

Option C:
Option C incorrectly adds F to the list of wrong statements. Statement F is in fact correct because prior studies provide a reference for interpreting current results. Grouping F with B and E misclassifies a true statement as wrong and makes the option invalid.

Option D:
Option D properly identifies B and E as the only wrong statements and leaves A, C, D and F untouched as correct. It reflects that review is needed before and during research and that expertise does not remove the need for systematic review. Therefore this combination is the correct answer.

Informed consent is a fundamental ethical requirement in research involving human participants. It means that individuals agree to take part voluntarily after being given adequate information about the study’s aims, procedures, potential risks, benefits and their right to withdraw at any time. This process respects participants’ autonomy and helps protect them from harm or exploitation. Since the stem emphasises voluntary participation following a clear explanation of the study, it is defining informed consent.

Option A:
Anonymity refers to a situation in which the researcher cannot link specific data to identifiable individuals because names or unique identifiers are not recorded. While anonymity is an important protective measure, it does not by itself cover the process of explaining the study and obtaining voluntary agreement. Thus, anonymity does not match the description provided.

Option B:
Informed consent requires researchers to communicate in language that participants can understand, answer their questions honestly and ensure that agreement is not obtained through coercion or undue pressure. Participants must also be informed of their rights, including the right to discontinue participation without penalty. These features correspond exactly to the scenario in the stem, which is why informed consent is the correct answer.

Option C:
Confidentiality involves protecting participants’ identities and the information they provide from unauthorised disclosure. It focuses on how data are stored, reported and shared rather than on the initial decision to participate. Although confidentiality is closely related to consent, the stem centres on the process of obtaining voluntary participation, so confidentiality is not the right term.

Option D:
Debriefing occurs after participation, especially when some degree of deception has been used in the study. During debriefing, the researcher explains the true purpose of the research and answers any remaining questions. This is different from the pre-participation explanation and agreement that define informed consent, so debriefing does not fit the stem.

Triangulation involves combining different approaches, such as interviews and surveys or quantitative and qualitative data, to study the same phenomenon. If findings converge across methods or sources, confidence in their validity increases. It can also help reveal complementary aspects of the research problem. Thus, the strategy of using multiple perspectives to cross-check results is correctly termed triangulation.

Option A:
Extrapolation means extending findings beyond the observed range of data or time period, often with caution. It does not inherently involve combining methods or sources for cross-checking. Therefore, it is not the best answer.

Option B:
Randomisation is the process of assigning participants to groups by chance to control bias, especially in experiments. While important, it does not refer to combining multiple sources of evidence. So it does not fit the stem.

Option C:
Option C, triangulation, emphasises convergence and complementarity across methods, observers or data sets. It is widely recommended to enhance credibility in both qualitative and mixed methods research. This aligns exactly with the description given, making the option correct.

Option D:
Replication refers to repeating a study or analysis, often with new samples, to see whether results hold. It deals with reproducibility over time rather than simultaneous use of multiple methods. Hence, it is not the correct completion here.