Ethical Data Analysis Checklist

Use this checklist before sharing an analysis.

1. Purpose
- What decision or learning question does this analysis support?
- Are all collected variables needed for that purpose?

2. Data quality
- Are missing values documented?
- Are measurement definitions clear?
- Are unusual values investigated before removal?

3. Sampling and bias
- Who is included in the data?
- Who may be missing?
- Could the collection method favor one group or channel?

4. Privacy and confidentiality
- Does the dataset include personal or sensitive information?
- Can identifiers be removed or restricted?
- Who should have access to the raw data?

5. Conflicts of interest
- Who benefits from a particular result?
- Are uncomfortable findings still reported?

6. Transparent reporting
- Name the source of the data.
- Explain the method in plain language.
- State limitations and what should not be concluded.

7. Recommendation
- Does the recommendation follow from the evidence?
- Is uncertainty visible?
- Is there a next step that can be tested or monitored?