Introduction to Statistical Methodologies
Statistical methodologies turn questions into structured analysis. By matching appropriate methods and visualisations to the data and purpose, they help reveal meaningful patterns, challenge initial assumptions and produce clear, evidence-based insights that support confident decisions.
Technique Overview
Introduction to Statistical Methodologies Definition
A statistical methodology is a structured approach to answering a question using data. It involves identifying the purpose of the analysis, selecting methods suited to the data, examining numerical and visual results, and interpreting the findings within their context. This approach helps ensure that analysis follows a reasoned process rather than relying on calculations alone (Wild and Pfannkuch, 1999; De Veaux, Velleman and Bock, 2021).
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Further Reading
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Introduction to Statistical Methodologies references (4 of up to 20) *
- Anscombe, F.J. (1973) ‘Graphs in statistical analysis’, The American Statistician, 27(1), pp. 17–21. doi: 10.1080/00031305.1973.10478966.
- De Veaux, R., Velleman, P. and Bock, D. (2021). Stats: Data and Models, Global Edition. Pearson.
- Kirk, A. (2024) Data Visualisation: A Handbook for Data Driven Design. 3rd edn. London: SAGE Publications.
- Matejka, J. and Fitzmaurice, G. (2017) ‘Same stats, different graphs: Generating datasets with varied appearance and identical statistics through simulated annealing’, pp. 1290–1294. doi: 10.1145/3025453.3025912.
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