Basic stance
Quantitative research grew out of the positivist tradition, which holds that social phenomena show regularities that can be observed objectively. It follows deductive logic: derive hypotheses from theory, collect data and decide whether the evidence supports or rejects them, usually aiming to generalise from a sample to a population.
Research process
- Define the problem and review the literature
- State hypotheses and operationalise variables
- Choose a design and a sampling plan
- Develop instruments and collect data
- Analyse statistically and test hypotheses
- Interpret and report
Main designs
- Experiments: random assignment and control groups to test causation.
- Quasi-experiments: comparison groups where randomisation is impractical.
- Surveys: questionnaires measuring attitudes and behaviour, either cross-sectional or longitudinal.
- Correlational studies: the direction and strength of associations.
Reliability and validity
Quality depends on consistent measurement (reliability) and measuring the intended concept (validity). Designs are judged on internal validity, the soundness of causal inference, and external validity, generalisability.
Strengths and limits
The approach is strong on objectivity, replication and large-scale generalisation, but can miss meaning, context and lived experience, so it is often combined with qualitative work in mixed-methods designs.
References
- Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE.
- Babbie, E. (2021). The Practice of Social Research (15th ed.). Cengage.
- Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin.
- Rubin, A., & Babbie, E. (2016). Research Methods for Social Work (9th ed.). Cengage.