Begin with the question and design
Statistical analysis starts with the research question, study design, sampling approach, and type of data. The same test is not appropriate for every dataset. Clarify the primary outcome, predictor variables, groups, repeated observations, and intended inference before selecting a method.
Prepare genuine, documented data
Use data collected and stored according to the relevant ethics and institutional requirements. Keep a data dictionary that defines variables, labels, units, codes, and missing-value conventions. Record exclusions and transformations. Never invent observations, change values to obtain significance, or hide inconvenient findings.
Check data quality and assumptions
Before analysis, examine duplicates, missingness, impossible values, coding errors, distributions, and whether the data structure matches the design. Statistical assumptions should be considered in context and reported transparently. If assumptions are not reasonable, discuss an appropriate alternative rather than forcing a preferred test.
Choose methods that answer the question
Descriptive summaries can characterize a sample; inferential methods may compare groups, assess association, or model outcomes. Regression, ANOVA, PCA, factor analysis, and structural equation modelling have distinct purposes and assumptions. Choice depends on design, measurement, sample, and research objectives.
Interpret outputs carefully
A p-value alone does not show the size or practical meaning of an effect. Consider estimates, uncertainty, model fit, assumptions, limitations, and the context of the question. Tables and figures should be clear, reproducible, and consistent with the reported methods. Statistical significance depends on the data and analysis and does not establish causation by itself.
Keep analysis reproducible
Where agreed, maintain analysis syntax or code, document software and decisions, and link outputs back to clearly identified variables. Keep a clean copy of the source data and avoid overwriting original records. Researchers should be able to explain and defend their own methods and conclusions.
Plan support responsibly
For a useful assessment, provide the question, design, variable list, data dictionary, and genuine de-identified data only through an agreed secure process. Confirm the requested deliverables in writing. Statistical support assists the researcher; it does not replace methodological judgment, ethical approval, or supervisor review.
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