UGC NET Questions (Paper – 1)

Statement C is wrong because extraneous variables are not simply irrelevant; they may influence the dependent variable and therefore often need to be controlled or accounted for in the design or analysis. Statements A, B, D and E are correct: the independent variable is manipulated or selected, the dependent variable is the measured outcome, control variables are held constant, and moderator variables can change the strength or direction of relationships. Hence, C alone is the incorrect statement and must be isolated as such.

Option A:
Option A is incorrect because it groups A, B and D as wrong, even though these three statements correctly define independent, dependent and control variables. Treating them as wrong would overturn standard terminology used in research methodology.

Option B:
Option B is correct because it identifies C alone as the wrong statement and implicitly accepts that A, B, D and E accurately describe the different roles variables can play. It highlights that extraneous variables require attention rather than dismissal.

Option C:
Option C is wrong because it combines C with D and thereby mislabels D as incorrect. Statement D rightly explains that a control variable is intentionally held constant to remove its influence on the dependent variable.

Option D:
Option D is also incorrect since it pairs C with E, wrongly suggesting that moderator variables cannot influence the relationship between independent and dependent variables. Statement E is actually a correct description of moderator variables.

Control variables are factors that the researcher deliberately holds constant or accounts for so that they do not confound the relationship between the independent and dependent variables. By stabilising these variables, the researcher reduces alternative explanations for observed effects. This enhances the internal validity of the experiment. Because the stem refers to variables kept constant to prevent them from influencing outcomes, it is describing control variables.

Option A:
Independent variables are intentionally manipulated to assess their impact on outcomes, not held steady. Their variation is central to testing hypotheses about cause and effect. Thus, independent variables are the opposite of what the stem indicates and cannot be the correct answer.

Option B:
Dependent variables are the outcomes measured to see whether they change as a result of the independent variable. They are expected to vary and are not kept constant. Since the question is about variables that are purposely held constant, dependent is not appropriate.

Option C:
A moderator variable influences the strength or direction of the relationship between independent and dependent variables, helping to specify “when” or “for whom” an effect is observed. Although researchers may sometimes create conditions based on moderators, the classic notion of control variables is more directly about holding factors constant. Therefore, moderator does not fit the stem’s description.

Option D:
Control variables are chosen and managed to remove their potential influence, such as keeping room temperature constant in a cognitive experiment. This deliberate stabilisation ensures that observed differences in the dependent variable are more likely due to the independent variable. These functions match the description in the stem, so control is the correct completion.

A directional hypothesis predicts the specific direction of an expected relationship or difference, such as stating that Method A will produce higher achievement than Method B. It leads to one-tailed statistical tests because the researcher is interested in deviations in a particular direction. This type of hypothesis is based on prior theory or evidence suggesting how results should differ. Since the stem mentions a hypothesis that specifies both existence and direction of difference, directional hypothesis is the correct term.

Option A:
A null hypothesis asserts that there is no significant difference or relationship between variables in the population. It does not predict a direction and often serves as the default assumption in significance testing. Therefore, null hypothesis does not fit the description in the question.

Option B:
Non-directional hypotheses merely state that a difference or relationship exists without indicating which group will score higher or what the direction of association will be. They correspond to two-tailed tests that consider both positive and negative differences. Because the stem emphasises specifying direction, non-directional hypothesis is not appropriate.

Option C:
A directional hypothesis can be more powerful statistically when correctly specified, but it also carries risk if the true effect is opposite in direction. It is justified when prior research strongly suggests a particular outcome. These features align closely with the stem’s description, so directional hypothesis is the right completion.

Option D:
A working hypothesis is a tentative assumption that guides the early stages of research and may or may not be directional. It is a broader term and does not necessarily indicate the explicit direction requirement highlighted in the stem. Hence, working hypothesis is not the best answer.

Random assignment is the process of allocating participants to experimental and control groups purely by chance, such as by using random numbers or drawing lots. It ensures that, on average, the groups are equivalent with respect to both known and unknown variables before the treatment is applied. This greatly strengthens internal validity by reducing selection bias. Because the stem highlights equal and independent chances of being placed in any group, random assignment is the correct term.

Option A:
Random assignment ensures that individual differences are distributed approximately evenly across groups, so observed post-treatment differences are more likely due to the intervention. It is a defining feature of true experimental designs. This role matches the stem’s description, confirming random assignment as the appropriate completion.

Option B:
Matching involves pairing participants who are similar on certain variables and then assigning them to different groups, which partially controls for those variables but does not guarantee equal independent chance of group placement for all participants. Thus, matching is not the correct answer.

Option C:
Blocking is used to control for the effects of one or more nuisance variables by forming homogeneous blocks and then randomly assigning treatments within each block, especially in agricultural or industrial experiments. While it involves randomisation, the stem’s focus on general equal and independent chances for all participants is more directly captured by random assignment.

Option D:
Clustering usually refers to grouping participants based on natural units such as classes or schools in sampling or design and does not necessarily imply random allocation of individuals to treatment conditions. As such, clustering is not the proper term for the procedure described.

A hypothesis is a provisional statement that proposes a possible relationship between variables which can be examined empirically. It guides the collection and analysis of data by indicating what the researcher expects to find. Because it is tentative, it must be subjected to testing and may be supported or rejected based on evidence. The stem clearly refers to such a testable statement, so the correct term is hypothesis.

Option A:
A hypothesis specifies expected relationships in a form that can be operationalised and statistically examined. For example, it might state that one teaching method will lead to higher achievement than another. This testable, tentative character distinguishes a hypothesis from broader, more established explanations and aligns exactly with the description given in the stem.

Option B:
A theory is a well-substantiated explanation of phenomena that integrates many findings and hypotheses into a coherent framework. Theories are broader and more established than individual tentative statements. Since the question emphasises a tentative statement to be tested, theory is too comprehensive to be the correct answer.

Option C:
A law is a statement describing a consistent, observable relationship that has been repeatedly confirmed, often expressed mathematically, especially in natural sciences. Laws are not tentative propositions in the same way hypotheses are; they are more stable generalisations. Thus, law does not fit the idea of a testable tentative statement in the stem.

Option D:
A construct is an abstract concept created for scientific purposes, such as intelligence, motivation or attitude. While hypotheses may involve constructs, the term construct itself does not mean a testable statement about relationships. Therefore, construct cannot complete the stem correctly.

The null hypothesis is a formal statement asserting that there is no effect, no difference or no relationship between variables in the population. It serves as the default assumption that researchers attempt to reject using sample data and statistical tests. If the evidence is strong enough, the null hypothesis is rejected in favour of an alternative explanation. Because the stem describes a statement of no significant difference or relationship, it clearly refers to the null hypothesis.

Option A:
A research or alternative hypothesis proposes that there is a meaningful effect, difference or relationship in the population. It is usually what the researcher hopes to support by rejecting the null hypothesis. Since the stem emphasises no difference or relationship, research hypothesis is opposite in meaning and therefore not correct.

Option B:
The null hypothesis states that any observed difference in the sample is due to chance and not to a real effect in the population. Statistical tests compute the probability of obtaining the observed data assuming this null hypothesis is true. When this probability is very low, the null hypothesis is rejected, which fits the description in the stem.

Option C:
A working hypothesis is a tentative assumption used to guide initial investigation and may or may not be formally tested statistically. It is a broader idea and does not necessarily state that there is no difference or relationship. Thus, working hypothesis is not the best completion for the definition given in the question.

Option D:
A directional hypothesis predicts not only that a difference exists but also the direction, such as which group will score higher. It is thus a type of research or alternative hypothesis, not the statement of no difference described in the stem. Therefore, directional hypothesis cannot be the correct answer here.

A case study is a detailed examination of a bounded unit such as a person, group, institution, programme or event over a period of time. It uses multiple sources like interviews, observations, documents and records to build a rich picture of the case. The emphasis is on depth of understanding in context rather than broad generalisation. Because the stem refers to intensive investigation of a single entity using multiple sources, case study is the correct term.

Option A:
Case studies allow the researcher to explore complex relationships and processes that might be missed in large-scale surveys or experiments. They are particularly useful when the phenomenon is unique, poorly understood or context-dependent. This focus on an in-depth exploration of a single case matches the description in the question, confirming case study as the appropriate answer.

Option B:
A survey typically collects data from a larger sample of individuals using questionnaires or interviews to describe trends or attitudes at a population level. It does not usually focus intensively on a single individual or institution. Hence, survey is not the correct completion here.

Option C:
An experiment manipulates independent variables and uses control groups to test causal effects under controlled conditions. Although experiments can be conducted on small samples, their purpose is not the holistic examination of a single bounded case through multiple evidence sources. Therefore, experiment does not fit the stem.

Option D:
Meta-analysis is a statistical technique that synthesises the results of multiple independent studies on a similar topic to produce overall effect estimates. It operates across many studies rather than concentrating on a single individual or institution. Thus, meta-analysis is not the right answer for this question.

A hypothesis proposes a specific relationship or difference between variables that can be examined empirically using data. It serves as a bridge between theory and observation by translating abstract ideas into testable propositions. In quantitative research, hypotheses guide the choice of design, measures and statistical tests. Therefore, a tentative, testable statement about expected relationships is correctly called a hypothesis.

Option A:
A theory is a broader system of concepts and propositions that explains a range of phenomena and often gives rise to many specific hypotheses. It is not itself usually framed as a single testable statement for one study, so it does not match the stem.

Option B:
Option B, hypothesis, typically includes clearly defined variables and sometimes indicates the expected direction of the relationship, such as positive or negative. Because it is explicitly testable, it can be supported or refuted through research findings, which aligns with the question.

Option C:
A law in science is a well-established generalisation that has been repeatedly confirmed and is widely accepted; it goes far beyond a tentative prediction in one study. Hence, law is not the appropriate answer.

Option D:
An assumption is a belief or condition accepted as true for the purposes of a study without direct testing. It does not necessarily describe an expected relationship that will be empirically examined, so it is not the best fit.

A research question is an interrogative statement that expresses what the researcher wants to know, framed in a way that can be investigated systematically. It provides direction for selecting methods, participants and analysis strategies. Good research questions are specific, feasible and significant. Because the stem describes a clear, focused and answerable interrogative statement that guides investigation, it is referring to a research question.

Option A:
A hypothesis is a declarative, testable proposition about relationships between variables that often arises from refining a research question. While related, a hypothesis is not itself interrogative. Since the stem emphasises an interrogative form, hypothesis is not the best answer.

Option B:
Objectives are declarative statements of what the researcher intends to achieve, typically beginning with verbs like “to examine” or “to compare.” They are not phrased as questions but as aims. Therefore, objective does not fit the interrogative nature highlighted in the stem.

Option C:
A proposition is a general statement that asserts a possible relationship or regularity, often used in theory development. It may be broader or less directly testable than a research question. The stem, however, focuses on a clear and answerable question guiding a specific investigation, pointing more precisely to a research question.

Option D:
Research questions translate broad topics into manageable inquiries that can be addressed with empirical methods. They play a crucial role in aligning literature review, method selection and analysis. This guiding function matches the stem’s description, confirming research question as the correct completion.

Internal validity refers to the degree to which a study is free from confounding influences and alternative explanations, so that changes in the dependent variable can be ascribed to the independent variable. High internal validity is achieved through control of extraneous variables, random assignment and appropriate design. It is crucial in experimental research where causal claims are being made. Because the stem describes attributing observed changes to the manipulation of the independent variable, internal validity is the correct term.

Option A:
External validity concerns the generalisability of findings to other populations, settings or times, rather than the correctness of causal inference within the study. A study can be internally valid but externally limited, so external validity does not match the stem.

Option B:
Ecological validity focuses on how well research findings reflect real-world behaviours and contexts, often associated with naturalistic settings. While related to generalisability, it is not about directly attributing effects to independent variables in a controlled design. Thus, ecological validity is not the appropriate completion here.

Option C:
Internal validity is enhanced by using control groups, randomisation and standardised procedures to isolate the effect of the independent variable. When these strategies are successful, researchers can more confidently claim that the treatment caused the observed outcomes. This is precisely what the stem is describing.

Option D:
Face validity simply indicates whether a test or study appears, on the surface, to measure what it claims to measure, as judged by laypersons. It does not address deeper issues of causal attribution and control over confounds, so it is not the correct answer.

A pilot study is a trial run of the main research project conducted on a smaller scale. It helps to identify practical problems in sampling, data collection tools and analysis procedures. Insights from the pilot are used to refine the design before the full study is launched. Therefore, a small preliminary feasibility study is correctly termed a pilot study.

Option A:
A case study is an in-depth analysis of a particular case such as an organisation or individual. It is not simply a small-scale test run of a larger research design. Hence, it does not match the function described in the question.

Option B:
A survey study is a full-scale investigation using questionnaires or interviews on a target population or sample. It is one substantive method rather than a preliminary test of procedures. So it is not the term used for a trial run.

Option C:
A pilot study specifically examines whether the planned methods, instruments and logistics work as expected. It can reveal ambiguities in questions, sampling difficulties and timing issues. Because of this feasibility-testing role, it fits the stem exactly.

Option D:
A longitudinal study follows the same participants over a long period to examine change, which is a full design rather than a short preliminary test. It does not primarily function as a feasibility assessment step. Therefore, it is not the correct option.

A quasi-experimental design resembles a true experiment in that the researcher introduces an intervention or treatment and measures its effect on an outcome, but it lacks random assignment of participants to conditions. Groups may be pre-existing intact classes or institutions, which can introduce selection biases. Researchers often use statistical controls or matching to reduce these threats. Because the stem describes manipulation of an independent variable without random assignment, quasi-experimental design is the correct term.

Option A:
Experimental design includes both manipulation of independent variables and the random assignment of participants to treatment and control groups, which allows strong causal inferences. The absence of randomisation in the stem makes experimental design an inaccurate label in this case.

Option B:
Ex post facto design studies differences that already exist without manipulating variables, so it is non-experimental; the researcher only observes and tries to infer possible causes from existing conditions. The stem, however, explicitly mentions manipulation of the independent variable, which does not occur in ex post facto designs.

Option C:
Correlational design examines the relationships between variables without manipulating them, using statistical associations to describe and sometimes predict outcomes. It does not meet the criterion of introducing a treatment or intervention as stated in the stem. Therefore, correlational design is not the best completion here.

Option D:
Quasi-experimental designs are common in educational and social settings where random assignment is impractical or unethical, yet some level of control and manipulation is still feasible. They provide more tentative causal evidence than true experiments but are stronger than purely observational studies, matching the description in the question.

A research design is a structured plan that links the research problem and questions to methods of data collection and analysis. It clarifies decisions about sampling, instruments, procedures and controls. A good design enhances the validity of conclusions by anticipating sources of error and specifying strategies to handle them. Therefore, the overall blueprint referred to in the stem is known as the research design.

Option A:
The design details whether the study will be experimental, correlational, descriptive or qualitative and indicates how variables will be measured and compared. Without a clear design, data collection may become unfocused and analyses inappropriate. This central planning role aligns exactly with the stem, making this option correct.

Option B:
A hypothesis is a tentative prediction or explanation about relationships between variables; it informs the design but is not the plan itself.

Option C:
A schedule usually refers to instruments such as interview schedules, not to the entire plan of the study.

Option D:
A scale is a measurement tool for quantifying attitudes or traits, such as a Likert scale, and is only one component of the larger design.

A conceptual framework organises key variables and constructs of a study into a visual or diagrammatic form, often using boxes to represent concepts and arrows to show presumed directions of influence. It is built from theory and prior research and illustrates the logic of how the researcher expects variables to be related. This framework guides the formulation of hypotheses, selection of measures and interpretation of findings. Therefore, the visual model described in the stem is accurately termed a conceptual framework.

Option A:
A sampling framework or sampling frame is the list or structure from which a sample is drawn and is not typically depicted as a network of variables and arrows. It concerns elements or units rather than theoretical relationships. Hence, sampling framework does not fit the stem.

Option B:
Operational framework would describe how constructs are operationalised or measured in practice, but this term is not commonly used to label the visual theoretical model of variables and relationships. It focuses more on procedures than on conceptual linkages, so operational framework is not the best completion.

Option C:
Statistical framework might refer to a set of assumptions and models used for data analysis, such as regression or multilevel models. While it involves variables, it is not necessarily represented as a box-and-arrow diagram outlining theoretical relationships. Thus, statistical framework is not the correct answer here.

Option D:
Conceptual frameworks help readers quickly grasp the structure of the research problem and the proposed causal or associative pathways, which is exactly the function described in the question.

In this question statements A, B, D and E reflect core features of research design, while statement C is incorrect. Statement A is true because a research design indeed acts as a blueprint guiding data collection, measurement and analysis. Statement B is correct since a well-planned design seeks to minimise bias and enhance the reliability of data, and statement D properly characterises descriptive designs as portraying characteristics of populations or phenomena. Statement E is also true as causal-comparative research explores cause–effect relationships without direct manipulation of independent variables, whereas statement C is false because even exploratory studies require at least a tentative design or plan.

Option A:
Option A includes A, B and E but leaves out D. Although A, B and E are correct, D is also a true statement about descriptive research designs. By omitting D, this combination does not include all the correct statements and so cannot be accepted as the right answer.

Option B:
Option B selects B, D and E but omits A. While B, D and E are accurate, excluding A means the crucial general idea of research design as a blueprint for the entire study is missing. A complete set of correct statements must include A as well, so this option is incomplete.

Option C:
Option C correctly groups A, B, D and E, all of which present a coherent understanding of research design and related types of studies. It omits statement C, which wrongly suggests that exploratory studies do not need any design. Since this option contains all and only the true statements, it is the correct answer.

Option D:
Option D adds statement C to the otherwise correct combination of A, D and E. Because C is false, claiming that exploratory studies never require a design, its inclusion makes the entire combination incorrect. A valid option cannot mix misleading statements with true ones, so this choice is not acceptable.