Evidence. Insight. Impact.Eldoret, Kenya   /   Working with you, wherever you areinfo@clarityresearch.co.ke ↗
Data & interpretation

Before the analysis, check the foundations.

A practical starting point for a transparent, question-led analysis process.

Return to the research questions

Decide which variables or qualitative material address each question. An analysis plan should explain what you want to learn, what evidence is available, and how each planned analysis contributes to an answer.

Understand how the data were generated

Record the sampling approach, collection tools, coding conventions, and units of measurement. Analysis cannot repair every limitation in the design or data collection process.

Document cleaning decisions

Check identifiers, missing values, coding consistency, plausible ranges, and duplicate records. Retain a protected original and record the changes made to the working dataset. Avoid silently removing inconvenient observations.

Match methods to the data

Choose methods based on the study design, type of data, research question, and relevant assumptions. For qualitative work, describe how material was coded and how interpretations were developed.

Interpret with care

Explain the size and meaning of a finding, the uncertainty around it, and the study limitations. A statistical relationship does not by itself establish a causal explanation. Include enough documentation for another person to understand the analytical choices.

A Clarity learning resource. Discuss your specific research or training needs with a suitably qualified adviser.
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