Types of Variables (Psychology Statistics)

Types of Variables in Psychology Statistics

• Binary Variable:

  • Represents two possible states, typically labeled as zero and one.
  • Examples include "improved/not improved" and "completed task/failed to complete task."

• Categorical Variable:

  • Indicates membership in categories; common in independent or predictor variables.
  • Examples include gender (male/female) and marital status (married/single/divorced/widowed).
  • Numerical labels may be assigned (e.g., 0 = male, 1 = female).

• Confounding Variable:

  • Obscures the effects of another variable, complicating causal relationships.
  • Example: Teaching methods (phonics vs. whole language) may confuse assessments of reading achievement.

• Continuous Variable:

  • Not confined to specific values, allowing for a range of outcomes measured on a scale.
  • Examples include reaction time, neuroticism, and IQ, which assume equal interval sizes.

• Control Variable:

  • An extraneous variable controlled to maintain focus on the primary variables of interest.
  • Also referred to as a covariate.

• Criterion Variable:

  • Represents the presumed effect in nonexperimental studies.

• Dependent Variable:

  • The presumed effect in experimental studies, influenced by the independent variable.
  • Should not be referenced in nonexperimental designs.

• Dichotomous Variable:

  • A synonym for binary variable, representing two categories.

• Discrete Variable:

  • Comprises only integer values, such as the number of trials required for a learning task.

• Dummy Variables:

  • Recodes categorical variables with multiple categories into binary variables for analysis.
  • For example, marital status can be divided into multiple binary variables to avoid misleading numerical assumptions.

• Endogenous Variable:

  • Part of the studied system, arising from within that system and influenced by other variables.

• Exogenous Variable:

  • Introduced from outside the system being studied and not affected by the system's internal conditions.

• Independent Variable:

  • The presumed cause in experimental studies, manipulated by the researcher while controlling for others.
  • Should not be used in nonexperimental contexts.

• Interval Variable:

  • A synonym for continuous variable, measured on equally spaced intervals.

• Intervening Variable:

  • Explains the relationship between other variables by providing a causal link.
  • Example: Medical care mediates the relationship between income and longevity.

• Latent Variable:

  • An underlying, unobserved variable hypothesized to exist and explain patterns in observed variables.