UGCNET Questions

In any research study, the population is the complete set of units about which the researcher wants to draw conclusions. Because studying all units is often impractical, a smaller group called a sample is selected from this population. The sample should represent the population so that inferences from sample data can be generalized appropriately. This distinction is fundamental to sampling theory.

Option A:
Option A incorrectly claims that population is always smaller than sample, which is logically impossible because a sample is drawn from the population. Samples are subsets and therefore cannot exceed the population in size.

Option B:
Option B clearly describes population as the full group of interest and the sample as a subset selected for actual study. This matches standard methodological definitions and underscores the logic of generalizing from sample to population.

Option C:
Option C states that sample and population are identical, which contradicts the very meaning of sampling. If they were identical, there would be no need to use sampling techniques.

Option D:
Option D incorrectly restricts the term “sample” to qualitative data and “population” to quantitative data. In reality, both populations and samples can involve any type of data; the distinction is based on whether we consider all units or only a subset.

Qualitative research is concerned with how individuals interpret and make sense of their world. It typically employs methods like interviews, observations and document analysis to capture rich, descriptive data. Studies are often conducted in natural settings to preserve context. Therefore, focusing on meanings and experiences is a hallmark of qualitative approach.

Option A:
Option A describes quantitative research, which uses numerical data and statistical techniques. While valuable, it is conceptually different from qualitative inquiry.

Option B:
Option B correctly emphasizes subjective meanings, participant perspectives and naturalistic context. These features align with interpretivist and constructivist orientations that underpin qualitative research. The aim is depth of understanding rather than numerical generalization.

Option C:
Option C again refers to quantitative research, where large random samples help achieve statistical generalization. Qualitative work usually relies on smaller, purposively selected samples.

Option D:
Option D suggests avoiding contact with participants, which is contrary to most qualitative designs. Qualitative researchers often engage closely with participants to co construct understanding.

Deductive reasoning proceeds from the general to the specific. In research, it usually starts with an existing theory or general principle and then derives specific hypotheses that can be tested empirically, allowing researchers to check whether observations support or contradict theoretical expectations.

Option A:
This option correctly describes deduction as starting with a general theoretical framework and narrowing down to specific statements about what should be observed. It reflects the classic sequence used in many quantitative studies.

Option B:
This option illustrates inductive reasoning, where patterns and theories emerge from specific observations; the researcher builds generalizations after examining particular classroom situations.

Option C:
Option C is another example of induction. Generating categories from interview transcripts without prior assumptions involves moving from detailed qualitative data to broader concepts or themes.

Option D:
Option D also reflects an inductive, exploratory approach in which the researcher enters the field without a guiding theory and allows patterns to emerge from the data, rather than deriving specifics from a prior general principle.

A Type I error, also known as alpha error, happens when the null hypothesis is actually true in the population but the sample evidence leads the researcher to reject it. In other words, the test concludes that an effect or difference exists when in reality it does not. The probability of committing this error is controlled by the chosen significance level, such as 0.05.

Option A:
Option A describes failing to reject a false null hypothesis, which is a Type II error (false negative), not Type I.

Option B:
Option B matches the formal definition of Type I error: incorrect rejection of a true null hypothesis, leading to a false positive conclusion.

Option C:
Option C refers to accepting (or failing to reject) a true null hypothesis, which is the correct decision and not an error.

Option D:
Option D portrays correct rejection of a false null hypothesis, which is the desired outcome of hypothesis testing rather than an error.

Experimental research aims to establish cause effect relationships by deliberately changing one variable and observing its effect on another. The researcher manipulates the independent variable while controlling or holding constant other variables that could influence the outcome. This control allows more confident inferences about causality. Thus, manipulation and control are central to experimental design.

Option A:
Option A involves secondary data analysis, which can be part of non experimental or correlational studies but does not by itself define experimentation.

Option B:
Option B correctly identifies the two core requirements: manipulation of an independent variable and control of extraneous factors. Without these, it is difficult to attribute observed changes in the dependent variable to the experimental treatment. Therefore, this feature is essential.

Option C:
Option C describes descriptive research, which observes and records phenomena without intervention. It does not satisfy the requirements of experimental design.

Option D:
Option D refers to large sample selection, which may be useful but is neither necessary nor sufficient for an experiment. Many experiments use relatively small samples yet retain strong internal validity.

Ethical research requires honesty in collecting, analyzing and reporting data regardless of whether results are favorable or expected. Unexpected or null findings still contribute to knowledge by challenging assumptions and guiding future inquiries, so they should be reported transparently with discussion of limitations and implications.

Option A:
This option advocates altering data, which is fabrication or falsification and a serious form of scientific misconduct that undermines trust in research.

Option B:
Suppressing unfavourable or null results contributes to publication bias and distorts the evidence base; it is unethical because it hides information that may be important for future studies or policy.

Option C:
This option is correct because it reflects scientific integrity: the researcher reports the actual findings, explores plausible reasons for the discrepancy with expectations, notes limitations and suggests how future work could build on these results.

Option D:
Rewriting the hypothesis after seeing the results without disclosure (HARKing) is misleading. It creates the false impression that the study was designed to test the observed pattern from the outset, which violates honest reporting standards.

A hypothesis expresses a researcher’s expectation about how two or more variables are related in the population. It is tentative because it may be supported or rejected after empirical testing. It is testable because it is stated in terms of observable variables that can be measured. By predicting direction or type of relationship, it guides the choice of design and statistical analysis.

Option A:
Option A is correct as it captures both tentative and testable nature and mentions prediction of relationships.

Option B:
Option B incorrectly treats the hypothesis as a final conclusion, whereas conclusions are drawn only after hypotheses are tested with data.

Option C:
Option C calls it a vague idea, but a proper hypothesis must be precise and operational, otherwise it cannot be tested scientifically.

Option D:
Option D confuses hypothesis with sampling details, which belong to the methodology section, not to conceptual predictions about variables.

Delimitations are conscious decisions made by the researcher to narrow the focus of the study. They specify aspects such as geographical area, time frame, population type or variables included. By stating delimitations, the researcher clarifies the scope and avoids overgeneralization. They are planned boundaries of the work, not flaws.

Option A:
Option A refers to limitations caused by factors beyond the researcher’s control, such as nonresponse or attrition. These are limitations, not delimitations.

Option B:
Option B correctly defines delimitations as chosen boundaries that structure the study. They inform readers about the context within which findings are valid and guide interpretation.

Option C:
Option C points to measurement errors, which are again limitations or problems rather than deliberate scope decisions.

Option D:
Option D concerns ethical issues, which are important but distinct from specifying the scope or boundaries of the study.

Research is essentially a systematic and objective investigation aimed at generating new knowledge or validating existing knowledge. It is driven by clearly defined questions or problems that require reasoned answers. Through careful collection and analysis of data, research attempts to provide solutions or explanations. Therefore, the central purpose of research is to expand understanding and address real or theoretical problems in a disciplined manner.

Option A:
Option A highlights the systematic and purposeful nature of research. It includes both the search for new knowledge and the attempt to solve identified problems. This aligns with standard definitions used in research methodology across disciplines. By stressing system and solution orientation, it correctly captures the fundamental purpose of research.

Option B:
Option B suggests data collection without an objective, which contradicts the requirement that research must be problem or objective oriented. Random data gathering does not qualify as scientific research. Without a clear purpose, analysis and interpretation become meaningless.

Option C:
Option C implies mere repetition of existing knowledge without verification or critical scrutiny. Genuine research involves testing, confirming, modifying or extending existing ideas, not simply restating them. Therefore, this option is incomplete and misleading.

Option D:
Option D reduces research to the production of lengthy reports for awards, which is only a byproduct and not the core purpose. Reports are communication tools for research findings, but research itself is about inquiry and understanding, not about document length or recognition.

Ratio scales possess all properties of interval scales plus a true zero point, allowing meaningful statements about ratios. Time taken to complete a test has an absolute zero and permits comparisons such as one student taking twice as long as another.

Option A:
This option describes a nominal variable, where categories represent different types without inherent order or equal intervals. Hostel and rented house are labels, not quantities.

Option B:
This option refers to ordinal data, where ranks indicate order but not equal differences between positions; you cannot say that the difference between rank 1 and 2 equals that between 2 and 3.

Option C:
Option C describes temperature in degrees Celsius, which is usually treated as an interval scale: differences are meaningful, but zero does not represent the complete absence of temperature and ratios (40°C is not “twice as hot” as 20°C) are not meaningful.

Option D:
Option D is correct because time in minutes has a true zero and equal units, so both differences and ratios are meaningful, satisfying the definition of a ratio scale.

A literature review enables the researcher to become familiar with what has already been done on a topic. By critically analyzing previous findings, the researcher can see what is known, where inconsistencies exist and what remains unexplored. This helps in sharpening the research problem, formulating appropriate objectives and avoiding unnecessary duplication.

Option A:
Option A suggests avoiding citations, which undermines scholarly honesty and disconnects the study from existing knowledge.

Option B:
Option B is correct as it highlights the three central functions: understanding existing knowledge, identifying gaps and refining the problem. These steps enhance relevance and originality of the research.

Option C:
Option C treats review as a mere way to increase length, ignoring its analytical and conceptual role in building a strong foundation for the study.

Option D:
Option D implies that literature review substitutes for methodology, which is incorrect. Methodology must still be explicitly designed and justified after reviewing literature.

Exploratory research is undertaken when the researcher has limited prior information about a problem situation. Its purpose is to gain familiarity, clarify concepts and identify promising directions for more structured studies. Rather than testing precise hypotheses, it helps generate them through flexible methods like informal interviews, case studies or pilot surveys. Therefore, exploration and idea generation lie at the heart of this design.

Option A:
Option A refers to hypothesis testing with large samples, which corresponds more to conclusive or explanatory research than exploratory work. Exploratory studies are usually small scale and flexible.

Option B:
Option B correctly describes exploratory research as focused on relatively unknown problem areas and aimed at producing insights, questions and tentative hypotheses. It emphasizes that the goal is conceptual and preparatory, not definitive testing or precise measurement.

Option C:
Option C talks about measuring the exact magnitude of a well defined phenomenon, which is more characteristic of descriptive or conclusive research rather than exploratory work.

Option D:
Option D stresses causal relationships and high control, which are features of experimental or explanatory designs rather than exploratory ones.

Self plagiarism occurs when an author reuses significant portions of their own previously published work without appropriate acknowledgment or permission. Republishing the same data and findings as if they were new misleads editors, reviewers and readers about the originality of the contribution and can distort the scientific record.

Option A:
This option represents good practice rather than misconduct. When researchers properly cite their earlier work, they transparently show how the new study extends previous efforts, which is acceptable.

Option B:
This option accurately describes self plagiarism because it involves reusing one’s own published findings without disclosure. The absence of cross-referencing creates the false impression that the work is entirely new.

Option C:
Using an established method from the literature with proper citation is normal scholarly practice. Because the original author is credited, there is no plagiarism, self or otherwise.

Option D:
Publishing extended versions of conference papers is acceptable when the earlier presentation is clearly acknowledged and the journal is informed. Transparent cross-referencing means this is not self plagiarism.

Experimental research aims to determine whether changes in one variable cause changes in another. This requires deliberate manipulation of the independent variable and control over other factors that might influence the outcome. By holding extraneous variables constant or randomizing them, the researcher can attribute observed differences in the dependent variable more confidently to the treatment.

Option A:
Option A describes qualitative interviewing, which is useful for exploration but does not by itself establish causality through controlled manipulation.

Option B:
Option B is correct because it combines the two essential ingredients of true experimentation: manipulation and control. Without these, causal claims remain weak or speculative.

Option C:
Option C refers to biased selection of participants, which can threaten internal validity and does not help in establishing causal relationships.

Option D:
Option D mentions very small samples and lack of control group, both of which weaken the ability to infer causality and generalize findings.

Research is understood as an organized process guided by clearly defined objectives and questions. It relies on systematic procedures for collecting, analyzing and interpreting data to address a problem or gap in knowledge. Objectivity and careful control of bias are emphasized to make the findings credible.

Option A:
Option A is correct because it includes the key features: planning, objectivity, systematic method and knowledge orientation. It covers both discovery of new knowledge and validation of existing knowledge through evidence.

Option B:
Option B presents research as casual and opinion based, which contradicts the disciplined nature of scientific inquiry.

Option C:
Option C reduces research to a single guess, ignoring the need for sustained investigation, data collection and analysis.

Option D:
Option D focuses only on data collection and neglects interpretation and reasoning, without which raw data cannot contribute meaningfully to knowledge.