What is Quantitative Research?
Quantitative research collects numerical data and analyses it statistically to describe, compare, find relationships or test causes. It asks "how much", "how many" and "what is the effect of" questions, measuring variables in ways that others can repeat.
Examples of Quantitative Research
- A survey of 1,200 university students on hours of paid work and exam results.
- A randomised trial comparing two reading programmes in 40 schools.
- An analysis of national census data on commuting times.
- School-level titles: "The relationship between screen time and sleep among Year 10 pupils"; "The effect of background music on memory test scores".
Types of Quantitative Research
- Descriptive: measures how common something is (a survey of reading habits).
- Correlational: tests whether variables move together, without showing cause.
- Causal-comparative: compares existing groups (for example, students who did or did not take a gap year).
- Quasi-experimental: tests an intervention without random assignment.
- Experimental: random assignment to conditions, the strongest test of cause (see experimental design).
Studies can also be cross-sectional (one point in time) or longitudinal (the same people over time).
Quantitative vs Qualitative Research
Quantitative research measures across many cases; qualitative research explores meaning in depth with fewer. Quantitative work is good at breadth and testing; qualitative at explaining why and discovering what to test.
Analysing Quantitative Data
- Descriptive statistics: means, percentages, standard deviations.
- Inferential statistics: t-tests, ANOVA, chi-square, correlation and regression, reported with effect sizes and significance.
- Software: SPSS, R, Stata, Python or Excel.
Quality: Reliability, Validity and Sample Size
Good quantitative research uses measures that are consistent (reliability) and measure what they claim (validity), and a sample size large enough to detect the effect of interest, ideally drawn by random sampling.
Strengths and Limitations
- Strengths: precise, comparable, able to generalise from good samples, and replicable.
- Limitations: can miss context and meaning, and is only as good as its measures.
Full guide: Qualitative vs Quantitative Research: 5 Real Studies
Use case: AI for research paper writing