liveBook · Manning

Mean

As explained in Prompt Engineering in Practice

The sum of a set of numerical values divided by the number of values.

The mean is the sum of numerical values divided by their count. In prompt sampling, it aggregates independent numeric outputs to reduce the influence of an outlier. section 8.2 section 8.0

Choose the aggregation method to match the output:

  • Use the mean for numerical outputs when variation could affect a decision. section 8.2
  • Use mode for categorical labels; use best-of-N when selecting one complete response. section 8.2

Runbook quality scoring

Generate four independent scores using a fixed prompt, then calculate their arithmetic mean: (7 + 8 + 7 + 6) / 4 = 7.0. Keep the spread as a secondary signal; a wider spread can prompt reviewer attention. section 8.2.1

Generation

Score

1

7

2

8

3

7

4

6

The four independent runbook scores used to calculate the mean. section 8.2.1

How Prompt Engineering in Practice covers it

How deep it goes
Defines when to use the mean and demonstrates its calculation; treats spread as a secondary signal and calculates the average manually.
Examples
Scores an incident runbook with four independent ratings of 7, 8, 7, and 6, yielding a mean of 7.0.
What it assumes
Assumes the prompt returns numerical outputs; the example uses a fixed scoring prompt and four independent generations.
What you can do after
Apply it by averaging independent numerical generations and retaining their spread as a signal for reviewer attention.
How it connects
Contrasts mean with mode for labels and best-of-N for complete responses, alongside self-consistency in prompt sampling.

Also explained in

Compare how 29 books explain mean →

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Prompt Engineering in Practice. The section links point to the parts of the book it draws on.