UGC NET Questions (Paper – 1)

Tabulation organizes coded data into tables that display frequencies, percentages or other summary figures. By arranging information in rows and columns, it allows researchers to see patterns, compare groups and prepare inputs for further statistical analysis.

Option A:
This option refers to storing raw questionnaires, which is a physical management task rather than analytical tabulation. Without classification and counting, no real analysis can begin.

Option B:
This option correctly captures tabulation as the systematic structuring of data into tables. It emphasizes both organization and the analytical purpose of facilitating comparisons and calculations.

Option C:
Increasing the number of questions in the questionnaire is a matter of instrument design and has nothing to do with the tabulation stage, which occurs after data are collected and coded.

Option D:
This option wrongly claims that tabulation ensures only qualitative data are collected. In practice, tabulation is used mainly for quantitative, coded data and can summarize both quantitative and categorized qualitative information.

Statements A, B, D and E outline common ICT support for research. Reference managers handle citations, spreadsheets and statistics software analyse quantitatively, online surveys gather data and cloud storage supports collaboration. Statement C is false because qualitative analysis software exists, and F is false because backups remain critical regardless of tools used. Therefore A, B, D and E only are correct.

Option A:
Option A is incomplete because it omits E and so does not mention the collaborative benefit of cloud storage for research teams. A, B and D are true but the set is not comprehensive.

Option B:
Option B is incorrect because it adds F, which wrongly suggests that backups are unnecessary when using ICT. This contradicts best practices in research data management, making the option invalid.

Option C:
Option C is incorrect because it leaves out A and includes only B, D and E. Without A, the role of reference management software is not represented, so the combination does not contain all correct statements.

Option D:
Option D is correct because it groups citation management, analysis tools, survey platforms and shared storage as essential ICT supports in research, while rejecting misconceptions about qualitative tools and backup needs.

Quantitative research is characterised by the use of structured instruments, numerical data and statistical procedures to test hypotheses or answer questions. It often seeks to establish patterns, relationships or differences among variables in large samples. The emphasis is on objectivity, measurement and generalisability. Hence, research that focuses on numerical data and statistical analysis is appropriately called quantitative research.

Option A:
Historical research involves systematic study of past events using documents and records, and it may use both qualitative and quantitative data. However, it is defined by its temporal focus rather than by emphasis on measurement and statistics alone. Therefore, historical research is not the best completion.

Option B:
Quantitative research commonly uses experiments, surveys and quasi-experiments to collect data that can be summarised with descriptive and inferential statistics. Its strength lies in producing generalisable evidence and estimates of effect sizes. This orientation aligns exactly with the description in the stem.

Option C:
Phenomenological research is a qualitative approach that explores lived experience and the essence of phenomena from participants’ perspectives. It typically uses in-depth interviews rather than extensive numeric measurement, so phenomenological is not the correct answer.

Option D:
Ethnographic research immerses the researcher in a cultural or organisational setting to understand practices and meanings, relying heavily on qualitative observations and narratives. It is not primarily about numerical measurement and statistical testing, so ethnographic does not fit the stem.

Tabulation involves organising raw data into tables where observations are summarised in rows and columns, often showing frequencies or summary statistics. This step converts unstructured responses into a form that is easier to inspect, compare and analyse statistically. Through tabulation, patterns and relationships in the data become more visible. Because the stem describes arranging data in rows and columns for analysis, it is defining tabulation.

Option A:
Tabulation creates a structured layout that can serve as the basis for graphs, charts and statistical computations. It is a key part of data processing after coding and editing have been completed. The focus on organising data into rows and columns matches the description in the stem, making tabulation the correct answer.

Option B:
Coding is the process of assigning numerical or symbolic codes to responses so that they can be handled by statistical software or summarised efficiently. While coding often precedes tabulation, it does not itself involve arranging data into rows and columns for analysis. Therefore, coding is not the appropriate completion here.

Option C:
Editing refers to checking raw data for completeness, consistency and accuracy, correcting obvious errors before further processing. It ensures data quality but does not primarily reorganise data into analytic tables. Thus, editing does not fit the stem’s definition.

Option D:
Sampling is concerned with selecting a subset of the population for study and occurs before data collection, not in the post-collection processing of data. It does not involve the mechanical arrangement of data into tables. Hence, sampling is not the right term.

Statements A, B, C and D correctly describe the four classical levels of measurement. Nominal scales simply classify, ordinal scales rank, interval scales provide equal units without a true zero and ratio scales include both equal intervals and an absolute zero. Statement E is false because nominal and ordinal data can still be analysed using appropriate statistics such as frequencies, medians and non-parametric tests. Therefore, the set containing A, B, C and D only is the correct combination.

Option A:
Option A includes A, B and C but omits D, thereby leaving out the crucial description of ratio scales, which are widely used for variables like height, weight or test scores with an absolute zero. Because it fails to list all the true statements, this option is incomplete.

Option B:
Option B is correct because it includes all four accurate descriptions of measurement scales and excludes E, which incorrectly claims that nominal and ordinal data are unusable in statistics. It gives a comprehensive and standard account of measurement levels.

Option C:
Option C includes E and omits A, which is a correct description of nominal scales. Since E is false and A is true, this combination misclassifies statements and cannot be accepted.

Option D:
Option D wrongly adds E, the false claim about unsuitability for analysis, and omits B, which correctly explains ordinal scales. Mixing a false statement with true ones and omitting a correct one makes the option invalid.

Option E includes E and leaves out C, neglecting the proper description of interval scales and accepting an incorrect restriction on nominal and ordinal data. Hence this option cannot be considered correct.

Quantitative research is characterised by the collection of numerical data that can be analysed using statistical techniques. It often begins with clearly stated hypotheses and variables that can be measured and tested. The goal is usually to examine relationships, differences or trends that can be generalised to a larger population. Because the stem describes numerical data and statistical hypothesis testing, it clearly refers to quantitative research.

Option A:
Qualitative research typically focuses on understanding meanings, experiences and processes through non-numerical data such as interviews, observations and documents. While it may use some counting, it does not primarily rely on statistical procedures to test predefined hypotheses. Therefore, qualitative research does not match the description in the stem.

Option B:
Historical research investigates past events and developments using records, documents and artefacts to interpret what happened and why. It may occasionally use numerical data, but its main emphasis is on chronological analysis and interpretation, not on hypothesis testing with statistical procedures. Thus, historical research is not the best fit here.

Option C:
Quantitative research designs, such as surveys or experiments, are built around measurement and statistical analysis. Researchers specify hypotheses, operationalise variables and collect data in a structured way to allow for statistical inference. Since the stem highlights these very features, quantitative research is the correct completion.

Option D:
Ethnographic research is a qualitative approach that involves prolonged immersion in a cultural or social setting to understand practices and meanings from the participants’ perspective. It usually produces rich descriptive narratives rather than primarily numerical, hypothesis-testing data. Consequently, ethnographic research is not what the question describes.