Reporting: turning outputs into decisions

Why this exists: Students often stop at plots. This chapter outlines the “so what?” layer Track D is aiming for.

Learning objectives

• Write short, evidence-based interpretations (not just numbers).

• Choose plots/tables that match the question.

• Communicate uncertainty and limitations clearly.

Outline

A simple reporting template

• Question → method → key results → interpretation → next step.

• Use the chapter’s *_summary.json + (when present) *_memo.md / *_executive_memo.md as your starting draft.

• Include 1–2 plots and 1 table, not 10.

What makes a good figure

• Readable axes, clear labels, one message per chart.

• Show comparisons (before/after, categories, distributions).

Common reporting failures

• Too many metrics with no narrative.

• No context: missing denominators, time windows, or baselines.

• Confusing accounting signs (debit/credit) with “good/bad”.

• Always state the sign convention you’re using (e.g., “positive = revenue inflow”).

Where this connects in the workbook

• GnuCash demo: daily totals + first analysis (example: daily totals → plots → interpretation)

• Track D Outputs Guide (artifact types and how to use them)

• Track D chapter index (PyPI) (see D09 for the plotting/reporting style contract)

Note

This page is intentionally an outline right now. Expand it incrementally as we refine Track D narrative.