# Answer Guidance — Summarizing Synthetic Reading Sessions

## Reader self-check

The numerical variables are `reading_minutes` and `quiz_score`. The sample has eight fictional observations. The computed output records the numerical summaries precisely; compare your terminal output to `expected-output.txt` rather than retyping values by hand.

A positive correlation in this tiny synthetic file means that larger invented reading-minute values are paired with larger invented quiz-score values in the sample. It is not evidence about actual learners, learning effectiveness, or causation.

## Publishing lesson

A companion-course release is stronger when the learning path and the proof materials are pinned together. A reader can obtain the exact dataset, run the exact script, compare deterministic output, complete the exercise, and consult versioned correction notes. That is the reason this open teaching module is packaged as a new `v0.2.0` release rather than silently changing the earlier metadata-only `v0.1.0` release.

## Boundary reminder

No real learner records, customer data, purchase gate, payment workflow, public deployment, or imported PyStatsV1 source code is involved in this example.