6 min readConcept sheetScale and source identification MCQs
Data: sources, types and classification
Data come from primary (collected first-hand) or secondary (already published) sources, and are quantitative (numbers) or qualitative (categories, words).
Primary dataCollected first-hand for the study
Secondary dataCollected earlier by others (Census, NSS reports)
QuantitativeDiscrete (counted) or continuous (measured)
Scales (NOIR)Nominal, ordinal, interval, ratio
Primary and secondary data
| Point | Primary | Secondary |
|---|---|---|
| Collected by | The investigator, for this study | Someone else, earlier, for another purpose |
| Typical sources | Survey, interview, questionnaire, observation, experiment | Census, NSS reports, RBI bulletins, journals, official records |
| Cost and time | High | Low |
| Fit to purpose | Exact | Must be checked for suitability and reliability |
Scales of measurement
| Scale | What it allows | Example |
|---|---|---|
| Nominal | Naming or grouping only; no order | Blood group, gender, religion |
| Ordinal | Order, but unequal gaps | Class rank, grades, ratings |
| Interval | Equal gaps, but no true zero | Temperature in °C, calendar year |
| Ratio | Equal gaps and a true zero | Height, weight, income, age |
Quantitative and qualitative data
QuantitativeNumbers that are counted or measured. Discrete: whole counts, such as number of students. Continuous: any value in a range, such as height.
QualitativeCategories, attributes or words: gender, opinions, interview transcripts. Analysed by coding into themes, or summarised as frequencies.
Classification and acquisition of data
- Geographical: by place, such as state-wise literacy.
- Chronological: by time, such as enrolment year by year.
- Qualitative: by attribute, such as gender or religion.
- Quantitative: by size, in class intervals such as income groups.
- Census method studies every unit; the sample method studies a representative part.
How NET asks this: identify the scale of measurement of a variable, tell primary from secondary sources, or classify data as discrete, continuous or qualitative.
Typical MCQ: “Temperature in degrees Celsius is measured on which scale?” Interval: equal gaps but no true zero, so 20 °C is not 'twice as hot' as 10 °C.
Typical MCQ: “Is Census of India data primary or secondary for a researcher?” Secondary: the Census organisation collected it, not the researcher.
NOIR (French for black): Nominal, Ordinal, Interval, Ratio. Each adds one property: order, then equal gaps, then a true zero.