Quantitative research

Quantitative research collects and analyzes numerical data to measure variables, test hypotheses, identify patterns, or estimate relationships. It uses structured measurement and statistical methods to support conclusions.

Operationalization: The process of defining abstract concepts as observable or measurable variables. It specifies how concepts such as trust or wellbeing become numerical data.
Variable (research): A measurable characteristic that can take different values across observations. Variables are the quantities researchers define, record, and compare.
Qualitative research: Research that interprets nonnumerical data to understand meanings, experiences, or social processes. It often explores meanings and context where numerical measurement is insufficient.
Randomized controlled trial: An experiment that randomly assigns participants to intervention and comparison groups. Random assignment can support estimates of an intervention’s causal effect.
Causal inference: The study of methods for estimating cause-and-effect relationships from data. Numerical association alone does not establish that one variable caused another.
Sampling (statistics): The selection of observations from a population for statistical study. Sampling determines which population a study’s measured results can represent.
Descriptive statistics: Methods for summarizing and presenting the main features of a dataset. They describe sample patterns before researchers make broader inferences.
Mixed-methods research: Research that integrates quantitative and qualitative methods within a study or program of inquiry. It combines numerical patterns with evidence about meanings or processes.
Quasi-experiment: A study estimating intervention effects without random assignment to conditions. It offers quantitative causal analysis when random assignment is infeasible or unethical.
P-value: The probability, under a specified null model, of data at least as extreme as those observed. Misinterpretation of p-values can turn statistical evidence into overstated claims.

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