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Demographic variables (e.g., age, education, and occupation) have been shown to be correlated with measures of intelligence (e.g., Barona, Reynolds, & Chastain, 1984; Wilson et al., 1978). Demographic predictors can be thought of in two ways.
Demographic variables are characteristics of a population that can be used to classify individuals, such as age, gender, income level, education, and marital status. These variables help researchers understand the composition of a population and identify patterns or trends within specific groups.
Demographics, the particular characteristics of a large population over a specific time interval. The word is derived from the Greek words for “people” (demos) and “picture” (graphy). Examples of demographic characteristics include age, race, gender, ethnicity, religion, income, education, home.
Usually demographics or research participant characteristics are reported in the methods section of the research report and serve as independent variables in the research design. Demographic variables are independent variables by definition because they cannot be manipulated.
Broadly defined, demography is the study of the characteristics of populations. It provides a mathematical description of how those characteristics change over time.
Demographic variables allow researchers to segment populations based on specific criteria, which can be essential for targeted marketing and policy-making. Changes in demographic variables over time can indicate shifts in societal trends, such as aging populations or changes in income distribution.
In research, some important demographic variables include: Type. Definition. Age. How old an individual is. Gender. Physical, social, or cultural characteristics relating to whether an individual identifies as male, female or an identity that does not correspond with neither male nor female, such as non-binary.
