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Precision

As explained in Experimentation for Engineers

Precision is the degree to which repeated estimates or measurements concentrate closely around their expected value.

Precision describes how closely repeated estimates or measurements cluster around their expected value. For individual measurements, variation may be uncontrollable; averaging repeated measurements produces a narrower distribution. section 2.2.1

Comparing execution costs

Aggregating 300 measurements gives ASDAQ 12.0003 and BYSE 10.0511, then repeated trials produce the same ordering. The aggregate standard deviations for sample sizes 3, 30, and 300 are 0.5722, 0.1807, and 0.0581.

How Experimentation for Engineers covers it

How deep it goes
Explains aggregation, distribution narrowing, sample-size effects, and standard-error calculation, but does not establish the unknowable expectation.
Examples
Uses NumPy measurements and repeated execution-cost comparisons between ASDAQ and BYSE.
What it assumes
Assumes familiarity with individual measurements, means, standard deviation, and square roots while treating the system as a black box.
What you can do after
Evaluate noisy alternatives by computing replicated means, comparing their spread, and reporting standard error.
How it connects
Connects precision with replication, aggregate measurements, expectation, standard deviation, and standard error.

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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Experimentation for Engineers. The section links point to the parts of the book it draws on.