Quantitative Research — Measuring the What
The productive tension
Statistical rigourandpractical relevance
The synthesis
The rigour camp insists on methodological purity: large samples, randomised selection, validated scales, statistically significant results. Without these, they argue, the findings are unreliable. The relevance camp insists on practical usefulness: fast answers, actionable insights, good-enough data to make the next decision. Without these, they argue, the research is an academic exercise that arrives too late to matter. Both are right about what matters and wrong about what can be sacrificed. Precision without purpose is waste -- statistically perfect answers to questions nobody is asking. But speed without rigour is recklessness -- acting on data that looks authoritative but is fundamentally unreliable. The researcher pursues rigour in service of relevance: methodologically sound research designed to answer the specific question the decision-maker needs answered, at the level of precision the decision requires, within the time the decision allows.
Learning objectives
- →Explain the epistemological logic of quantitative research and its relationship to generalisation and hypothesis testing
- →Evaluate the strengths and limitations of survey research, panel data, and experimental designs in marketing contexts
- →Apply sampling theory to distinguish between representative and biased samples and explain why sample quality matters more than sample size
- →Identify common sources of bias in quantitative research including response bias, social desirability, and non-response bias
- →Articulate the Both/And of statistical rigour and practical relevance, recognising that precision without purpose is waste
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