UGC NET Questions (Paper – 1)

Empirical research is grounded in data obtained through direct observation, experience or experiment. It emphasises verifiable evidence rather than purely speculative reasoning. Findings are supported by systematically collected and analysed data. Therefore, research that relies on observation or experience is correctly termed empirical research.

Option A:
Option A refers to empirical research, which uses sensory or instrumental observations as its primary source of knowledge. It involves collecting data from the field or laboratory in a systematic manner. This option matches the description of relying on real-world phenomena and is therefore correct.

Option B:
Conceptual research focuses on developing new ideas, concepts or theoretical frameworks without necessarily collecting primary empirical data. It may rely heavily on logical reasoning and existing literature. Because it is not defined mainly by direct observation or experience, it does not fit the stem.

Option C:
Philosophical research examines fundamental questions about knowledge, reality and values using logical analysis and argument. It is primarily reflective and critical rather than data-driven in the empirical sense. Hence, it does not describe research based chiefly on observation and experience.

Option D:
Historical research reconstructs past events using documents, records and other traces. Although it may use evidence, its purpose is to understand history rather than to observe current real-world phenomena for empirical generalisation. So it is not the best label for the kind of research asked in the question.

Statements A, B, C and E all describe accepted forms and benefits of triangulation. Researchers may combine different data sources, methods and investigators to cross-check evidence, and this typically enhances the credibility and robustness of results. Statement D is false because theory triangulation involves considering multiple theoretical perspectives, not ignoring them. Hence, the correct combination includes A, B, C and E and excludes D.

Option A:
Option A includes A, B and C but omits E, failing to mention explicitly that the main purpose of triangulation is to strengthen credibility and confidence in findings. Without E, the rationale for using triangulation remains incomplete.

Option B:
Option B contains B, C and E but leaves out A, so it does not refer to data triangulation, which is an important dimension involving varied data sources. This absence means the option does not capture all key forms of triangulation.

Option C:
Option C is correct because it assembles the three main forms of triangulation mentioned and links them with the overarching purpose of improving credibility. It rightly excludes D, which misinterprets theory triangulation as ignoring alternative perspectives.

Option D:
Option D includes A, C and E but omits B, overlooking method triangulation, which is commonly used when combining, for example, interviews and questionnaires. Without B, the picture of triangulation types is incomplete.

Good research follows a planned and organized procedure instead of haphazard steps. It uses logical reasoning to link concepts, methods and conclusions. Empirical evidence, collected through appropriate tools, supports or refutes the researcher’s propositions. These features together ensure that research findings are credible, verifiable and useful.

Option A:
Option A overemphasizes personal preferences, which can introduce bias and subjectivity. While researchers’ interests matter in topic selection, sound research cannot be guided only by personal likes or dislikes. It must conform to methodological standards beyond individual preferences.

Option B:
Option B correctly combines systematic planning, logical reasoning and reliance on empirical data. These elements are repeatedly emphasized in research methodology texts as marks of quality inquiry. By grounding conclusions in observable evidence and coherent argument, this characteristic distinguishes good research from casual opinion.

Option C:
Option C highlights unverified assumptions and guesses, which may serve as starting ideas but cannot remain unexamined. Research must test assumptions rather than rely on them blindly. If guesses are not subjected to evidence, the work remains speculative rather than scientific.

Option D:
Option D suggests avoiding literature, which would isolate the study from existing knowledge. A good study always situates itself in prior work to avoid duplication, build on established findings and identify gaps. Ignoring literature reduces both relevance and rigor.

The mean is calculated by summing all scores and dividing by the number of observations, so every value contributes to its magnitude. As a result, extremely high or low scores can pull the mean toward them, distorting its representation of the typical value. This sensitivity makes the mean less robust in skewed distributions. Because the stem asks for the measure most affected by extreme scores, mean is the correct answer.

Option A:
Median is based on the middle position of ordered scores and is largely unaffected by the exact values of extremes, as long as their positions do not change. It is therefore more robust to outliers than the mean. Hence, median does not match the property described in the stem.

Option B:
Mean provides useful information in symmetric distributions with few outliers but becomes misleading when the data are highly skewed, such as income distributions. In such cases, median or trimmed means are often preferable. The strong impact of extreme scores on mean corresponds to the statement in the question, confirming mean as the appropriate completion.

Option C:
Mode identifies the most frequent score in the distribution and is not calculated using all values. While the presence of outliers can alter frequencies, extreme scores are not inherently more influential than other scores. Thus, mode is not the measure that is most affected by extremes in the sense described.

Option D:
Geometric mean is used mainly for multiplicative processes or growth rates and, although sensitive in its own way, is not the standard measure considered in discussions about the influence of extreme scores on central tendency in basic descriptive statistics. Therefore, geometric mean is not the best answer here.

Coding involves transforming raw responses into a format suitable for analysis, usually by assigning numeric or symbolic codes to each category of response. This step enables efficient data entry into statistical software and facilitates counting, classification and comparison. Predetermined coding schemes ensure consistency across cases and variables.

Option A:
This option describes tabulation, which occurs after coding and refers to arranging coded data in table form; it depends on coding but is not the same process.

Option B:
This option precisely defines coding as assigning symbols or numbers to categories based on a coding frame. It captures the preparatory role of coding in converting raw qualitative or categorical information into analyzable units.

Option C:
Drawing graphs and charts is part of data presentation and sometimes analysis. It uses data that have already been coded and tabulated; it is not itself the coding step.

Option D:
Writing descriptive summaries of interview transcripts is a qualitative analysis activity such as theming or narrative description. It may follow coding but is not what “coding of research data” means in standard quantitative processing.

Problem identification is the starting point of any research endeavour because it recognises a gap, difficulty or unsatisfactory condition that requires investigation. By articulating this felt difficulty, the researcher frames what needs to be studied and why. This step guides the selection of objectives, hypotheses and methods that follow. Therefore, the first step involving recognition of an area of concern is accurately termed problem identification.

Option A:
Data analysis occurs after data have been collected and involves organising, summarising and interpreting numerical or qualitative information. It is a later stage in the research process and depends on an already formulated problem and design. Hence, data analysis cannot be the first step described in the stem.

Option B:
Hypothesis testing is a subsequent stage where tentative predictions derived from the problem and literature are examined using data and statistical procedures. It presupposes that the problem has already been identified and operationalised. Thus, hypothesis testing is not the initial step mentioned in the question.

Option C:
Problem identification converts a vague sense of difficulty into a clear statement that can be addressed systematically. It may emerge from practice, theory or literature and sets the direction for the entire study. This priority role makes problem identification the correct term for the blank.

Option D:
Report writing is the final stage where the completed study is documented and communicated to others. It presents the problem and findings but does not initiate the research process, so it is not the first step asked for in the stem.

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.

Ethical research respects the autonomy and dignity of participants. Informed consent requires that individuals receive adequate information about the study and participate voluntarily. Researchers must also safeguard privacy, confidentiality and safety, minimizing any potential harm. Together, these responsibilities embody respect for persons and beneficence.

Option A:
Option A suggests systematic deception, which may be used in limited circumstances but never as a general principle. Even when minimal deception is used, participants must be debriefed and protected from harm.

Option B:
Option B is correct because it combines informed consent, voluntariness and protection of welfare, which are emphasized in major ethical codes such as the Belmont Report and institutional review guidelines.

Option C:
Option C proposes coercion, which violates the right to withdraw at any time without penalty. Compulsory participation is ethically unacceptable.

Option D:
Option D disregards confidentiality and privacy, exposing participants to potential social, legal or psychological harm.

Measures of dispersion indicate the extent to which scores differ from each other and from the central tendency. Standard deviation summarizes the average distance of scores from the mean; a larger value implies greater variability, while a smaller one indicates tighter clustering.

Option A:
This option is correct because standard deviation directly quantifies spread around the mean. It is routinely reported in research articles to describe variability and underpins many inferential statistics.

Option B:
This option, the arithmetic mean, is a measure of central tendency, not dispersion. It reports the average level of scores but not how spread out they are.

Option C:
The median is also a measure of central tendency. It indicates the middle score but does not describe whether the other scores are close together or widely scattered.

Option D:
The mode shows which score occurs most frequently, but it gives no information about how far other observations deviate from that value, so it is not a measure of dispersion.

Statements A, B, C, E and F are correct, whereas D is false. Statement A is true because statistical packages automate many calculations and reduce manual errors. Statement B is correct since reference managers store and format citations, and statement C rightly states that qualitative software aids coding and retrieval. Statement E is accurate because plagiarism-detection tools reveal textual overlaps, and statement F is true as data privacy is a key ethical concern, while D is false because software cannot replace researcher judgement in interpreting results.

Option A:
Option A lists A, B and C but omits E and F, thereby ignoring issues of plagiarism detection and data privacy. While the included statements are correct, the set does not cover all true statements from the list and is thus incomplete.

Option B:
Option B contains B, C and E but leaves out A and F. Excluding the role of statistical software and privacy concerns means the combination fails to present a comprehensive account of computer use in research. Therefore it cannot be considered correct.

Option C:
Option C correctly groups A, B, C, E and F and excludes D, which wrongly denies the essential role of researcher judgement. It addresses computational support, referencing, qualitative analysis, plagiarism checking and privacy. Because it contains all and only the true statements, this option is the correct answer.

Option D:
Option D includes D along with the correct statements and so becomes invalid. By implying that software can replace researcher judgement, it contradicts responsible research practice. Any option containing D cannot represent a fully correct set of statements.

Statements A, B, D and E correctly describe research communication practices. Conferences provide early feedback, journals typically apply more formal peer review, journal choice should align with scope and aims and clear writing that follows author guidelines improves acceptance chances. Statement C is false because repeatedly presenting the same paper without disclosure can be considered unethical or at least questionable, as it may waste limited programme slots and mislead organisers. Hence, the combination including A, B, D and E and excluding C is correct.

Option A:
Option A is correct because it recognises the complementary roles of conferences and journals, the importance of scope matching and the need for clarity and compliance with guidelines, while rejecting the idea of undisclosed repeated presentations as acceptable.

Option B:
Option B is incomplete since it omits E, overlooking the influence of clear writing and adherence to guidelines on editorial decisions. Without E, the author’s responsibility in improving acceptance chances is underplayed.

Option C:
Option C is wrong because it leaves out A and includes only B, D and E, thereby ignoring the valuable feedback function of conferences in refining work before journal submission.

Option D:
Option D is incorrect as it includes C, the statement that normalises undisclosed duplication, alongside A, D and E. By accepting C, this option fails to uphold ethical norms in scholarly communication.

The null hypothesis serves as a default position stating that any observed difference or association in the sample is due to chance. It posits no real effect, no difference or no relationship at the population level. Statistical tests assess whether the sample data provide enough evidence to reject this assumption. Thus, H0 represents the benchmark against which alternative claims are evaluated.

Option A:
Option A correctly captures the idea that the null expresses absence of effect or relationship. It is framed in a way that can be tested using probability models and sampling distributions. If evidence contradicts H0 beyond a chosen significance level, it may be rejected.

Option B:
Option B suggests that the null is what the researcher wants to prove at any cost, which is incorrect. Researchers often hope to reject the null in favor of their alternative hypothesis, but they must do so based on evidence, not desire.

Option C:
Option C claims that the null cannot be tested, which contradicts its very role in inferential statistics. Hypothesis tests are structured specifically around assessing H0.

Option D:
Option D concerning sample size is unrelated to the content of the null hypothesis. Sample size affects power but is not itself expressed in H0.

Statements A, C, D and F describe key features of a good research problem. Statement A is true because a problem must be researchable given methods and resources. Statement C is correct since significance for theory or practice justifies the effort, and statement D is right that clear delimitation in terms of variables and context is necessary. Statement F is also true because many problems emerge from field experience or theoretical gaps, whereas B is false since the solution should not be known in advance and E is false because problems should be clearly, not vaguely, stated.

Option A:
Option A includes A, C and D, which are correct, but leaves out F. Since F correctly notes that research problems may arise from practice or theory gaps, omitting it makes the combination incomplete. A correct option must contain all the true statements identified in the list.

Option B:
Option B focuses on C, D and F and leaves out A. While C, D and F are true, A is also correct because feasibility in terms of methods and resources is an essential criterion. By excluding A, this option offers only a partial description of a good research problem.

Option C:
Option C correctly combines A, C, D and F and excludes the false statements B and E. It captures feasibility, significance, clear delimitation and genuine origin of problems, which together reflect sound research practice. Because it contains all and only the true statements, this is the correct answer.

Option D:
Option D brings in E alongside the otherwise correct statements. However, E is false because vagueness in problem statement leads to conceptual confusion and weak design. Including an incorrect statement makes this combination unacceptable.

Statements A, B, C and E correctly describe common differences and relationships between theses and journal articles. Theses tend to be lengthy, with detailed methodology and background, and are examined by internal or external examiners. Journal articles are concise, often with strict word limits, and scholars frequently adapt thesis findings into publishable articles. Statement D is false because peer review is a central process for most academic journals.

Option A:
Option A is correct because it includes all four true statements and excludes D, which misrepresents the nature of journal publication. It reflects how theses function as comprehensive research reports, while articles disseminate condensed versions to wider audiences.

Option B:
Option B is incomplete because it omits E, ignoring the common practice of transforming thesis chapters into journal manuscripts. Without E, the option does not capture the dynamic relationship between the two forms of publication.

Option C:
Option C includes B, C and E but excludes A, failing to mention the distinctively detailed character of thesis methodology and background chapters. This omission leaves an important structural difference unexplained.

Option D:
Option D contains A, C and E but leaves out B, so it does not mention that journal articles are usually tightly constrained in length. As word limits shape article structure, this omission makes the option incomplete.

Exploratory research is used at the early stage of investigation when little is known about a topic or when the researcher seeks to clarify the nature of the problem. It relies on flexible, open-ended methods such as informal interviews, focus groups or small-scale studies to generate insights and possible hypotheses. The emphasis is on breadth of understanding rather than on rigorous testing. Because the stem refers to gaining familiarity and generating ideas when the problem is not clearly defined, exploratory research is the correct term.

Option A:
Explanatory research focuses on testing specific hypotheses about causal relationships, which typically occurs after basic familiarity with the problem has been established. It is more structured than the kind of preliminary work described in the stem, so explanatory research is not appropriate here.

Option B:
Evaluative research assesses the effectiveness or value of programmes, policies or interventions, usually with clearly specified criteria and outcomes. It is not primarily about clarifying poorly defined problems or generating new ideas, so evaluative research does not match the stem.

Option C:
Historical research looks at past events and developments to understand how present conditions came to be, using archival sources. While it may generate ideas, it is not specifically defined as a method for exploring unclear current problems, so it is not the best completion.

Option D:
Exploratory research often informs the formulation of more precise questions, hypotheses and designs for subsequent descriptive or explanatory studies. This role as an initial step fits the description given in the question.