Missing at random
Definition
Missing at random is a statistical or measurement concept used to describe, compare, or interpret engineering data. Its meaning depends on the unit of analysis, data-generating process, and question being asked.
What Missing at random captures
Missing at random is a statistical or measurement concept used to describe, compare, or interpret engineering data. In practice, the useful question is what the value represents, which observations contribute to it, and what alternative explanations remain. Write down the unit, inclusion rule, and aggregation before comparing results.
An engineering example
A delivery dataset lacks some review or deployment observations. The missing at random helps describe the missingness or measurement problem, while the team reports affected units and checks whether conclusions change under reasonable alternatives.
Limits and interpretation
The handling choice can change who remains represented and how much uncertainty is retained. A clean-looking dataset is not proof that the missingness mechanism is harmless.
Use the result responsibly
Pair this concept with the underlying observations, sample count, comparison condition, and uncertainty. Preserve the query or calculation version when the result informs a release, staffing, reliability, or AI adoption decision. If the definition changes, mark the boundary so a trend is not confused with a measurement change.
How this relates to Weave
In Weave, missing at random can help frame analysis of engineering activity, delivery outcomes, or AI-assisted work in context. Use it to inspect relevant events, cohorts, and time windows rather than reading a summary in isolation. Weave can connect work signals, but it does not by itself establish causality, repair incomplete instrumentation, or guarantee that a metric represents business value.
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