Quantitativ

Quantitativ describes a class of research approaches that emphasize measurement and numerical representation of phenomena. In English, the corresponding term is quantitative. Quantitative methods rely on predefined metrics, standardized procedures, and numerical data to assess properties, relationships, or effects across populations or samples.

Quantitativ research collects data through structured instruments such as surveys, tests, experiments, and observational checklists. Data are typically numerical: counts, scores on scales, or continuous measurements. Analyses focus on describing data and testing hypotheses using statistics, including descriptive statistics, hypothesis testing, regression, and multivariate methods. Experimental designs often feature randomization and control conditions.

Strengths include higher generalizability, objectivity, replicability, and the ability to identify patterns and causal relationships under controlled conditions. Limitations include potential neglect of context and meaning, overreliance on measurement validity, sampling biases, and challenges in capturing complex or rare phenomena. The quality of conclusions depends on measurement quality and sampling design.

Quantitative methods are frequently complemented by qualitative methods in mixed-methods research, where numerical results are enriched by contextual insights. Instrument development, pilot testing, and pre-registration are common practices to improve rigor and transparency.

Etymology: from Latin quantitativus, via European languages; the corresponding adjective form in many languages is quantitativ, and the English noun is quantitative.