Kinds of Quantitative Research & Classifying Variables

Vocabulary flashcards covering key terms related to kinds of quantitative research and variable classifications discussed in the lecture.

Quantitative Research

A systematic investigation that focuses on collecting and analyzing numerical data to explain phenomena.

Non-Experimental Research

Quantitative studies that observe and analyze naturally occurring variables without manipulation.

Descriptive Research

A non-experimental approach aiming to portray characteristics of a population or phenomenon (e.g., survey of study habits).

Correlational Research

A non-experimental design that examines the relationship between two variables without establishing causation.

Causal-Comparative / Ex Post Facto Research

A non-experimental method that infers causes by comparing pre-existing groups on a dependent variable.

Experimental Research

Studies that manipulate an independent variable, control extraneous factors, and use random assignment to establish cause-and-effect.

True Experimental Design

An experimental study with random assignment, a control group, and deliberate manipulation of the independent variable.

Quasi-Experimental Design

An experimental approach without random assignment; may lack a control group and has limited manipulation.

Variable

Any measurable factor, trait, or condition that can vary and is measured, controlled, or manipulated in research.

Categorical Variable

A variable describing qualities or characteristics (e.g., gender, eye color) rather than numeric amounts.

Ordinal Variable

A categorical variable whose categories have a logical order or rank (e.g., poor–average–excellent).

Nominal Variable

A categorical variable with categories that lack intrinsic order (e.g., religions, languages).

Dichotomous Variable

A categorical variable with exactly two categories (e.g., yes/no; male/female).

Polychotomous Variable

A categorical variable with more than two categories (e.g., educational attainment levels).

Numeric Variable

A variable that represents measurable numerical quantities, answering "how many" or "how much."

Continuous Variable

A numeric variable that can assume any value within a range, including fractions (e.g., height, temperature).

Discrete Variable

A numeric variable that takes only whole numbers (e.g., number of children, registered cars).

Experimental Variable

A variable involved in manipulated studies; includes independent and dependent variables.

Independent Variable

The manipulated or explanatory variable in an experiment (e.g., amount of fertilizer).

Dependent Variable

The response or outcome affected by the independent variable (e.g., plant growth).

Non-Experimental Variable

Variables in observational studies; divided into predictor and criterion variables.

Predictor Variable

A non-experimental variable thought to influence another variable (e.g., social media usage level).

Criterion Variable

The outcome variable influenced by the predictor in non-experimental research (e.g., learning satisfaction).

Extraneous Variable

A pre-existing factor that may influence study results; also called confounding, mediating, or intervening variable.

Confounding Variable

An extraneous variable that varies with the independent variable, potentially distorting causal conclusions.

Mediating / Intervening Variable

Alternate names for extraneous variables that intervene between independent and dependent variables.

Cause-and-Effect Relationship

A connection established when manipulation of one variable (cause) produces changes in another (effect).

Random Assignment

Placing subjects into groups by chance to equalize extraneous factors in true experiments.

Research Problem

A focused question or issue a study seeks to answer, informed by identifying relevant variables.

Importance of Identifying Variables

Clarifies what will be measured, guides data collection, and leads to focused interpretations in quantitative studies.