Revision summary
A variable is a property with more than one value across cases. Independent, dependent, intervening and control names mark their role in a design. Stevens’s nominal, ordinal, interval and ratio levels mark how they are measured. Qualitative categories differ from quantitative counts and scales. A worked example is women’s education, fertility, age at marriage and wealth as control. Indian large surveys such as NFHS use this same grammar.
Model answer
Introduction
A variable is a property that can take more than one value across persons, groups or times. Age, caste category, years of schooling, income, religiosity and vote choice are variables; a proper name is not. In social research the point of naming variables is to state a relationship that can be observed, compared and, where appropriate, measured. Without that step, a hypothesis remains a slogan.
Body
Role in the research design
The independent variable is the presumed condition or cause that the researcher treats as input. The dependent variable is the outcome to be explained. An intervening or mediating variable sits on the path between them. A control or extraneous variable is held constant, statistically or by design, so that a spurious link is not mistaken for a cause. Paul Lazarsfeld’s elaboration model taught sociologists to introduce a third variable and see whether the original association survives.
Take literacy and fertility. Education of women may be independent; number of children dependent. Age at marriage and knowledge of contraception may intervene. Rural or urban residence, caste and household wealth are controls. If the education–fertility link vanishes after wealth is controlled, the first story was incomplete.
Types by measurement and nature
Variables are also typed by how they are scaled. S. S. Stevens’s levels remain the classroom kit: nominal (religion, gender as categories), ordinal (class self-placement, Likert agreement), interval and ratio (income, years of schooling, age). Qualitative or categorical variables sort cases; quantitative variables number them. Discrete counts (number of rooms) differ from continuous measures (income). Dummy variables turn a category into 0/1 for regression.
In Indian survey practice, NFHS and NSS/PLFS live on this vocabulary. A researcher who confuses a control with a dependent variable, or treats caste as a ratio scale, has not yet begun valid analysis. Variables are the grammar of hypothesis, sampling and table-making.
Flow diagram
flowchart LR IV[Independent] --> INT[Intervening] INT --> DV[Dependent] CV[Control] -.-> DV IV -.-> DV
Conclusion
A variable is a varying social property placed in a design as cause, effect, path or control, and scaled as category or number. The examiner wants types with a worked relation, not a dictionary list. Clear variables make reliability and hypothesis testing possible.
Quick related
Students also ask
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Is caste a quantitative variable?
Usually it is treated as a nominal or ordinal category. Treating it as a ratio score would be a measurement error.
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What is an intervening variable?
A factor on the causal path, such as age at marriage between women’s education and fertility.
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