Capstone rubric (100 points)
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This rubric is meant to be transparent and practical.
It rewards (1) correct reconciliations and (2) clear, decision-ready communication.

1) Controls & reconciliation quality (25 pts)
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* **25–22**: Reconciliations complete, reconciling items correctly categorized, clear
  corrections log, strong exception checks, and a clean audit trail.
* **21–16**: Mostly correct; minor gaps, light documentation, or a few unclear tie-outs.
* **15–0**: Material errors, missing tie-outs, weak audit trail, or unclear corrections.

2) Data preparation & documentation (20 pts)
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* **20–18**: Clean, tidy dataset; clear data dictionary; assumptions log; reproducible steps.
* **17–12**: Dataset usable but inconsistent naming/definitions or weak documentation.
* **11–0**: Messy data; unclear sources/definitions; not reproducible.

3) Statistical analysis & interpretation (20 pts)
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* **20–18**: Correct methods; practical interpretation; avoids causal overreach;
  highlights uncertainty and diagnostics.
* **17–12**: Reasonable analysis but some interpretation issues, missing diagnostics,
  or limited linkage to business meaning.
* **11–0**: Incorrect/irrelevant methods; misleading claims; no uncertainty handling.

4) Forecast quality & forecast hygiene (25 pts)
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* **25–22**: Forecast ties across statements; includes backtesting; error metrics;
  scenario logic; governed assumptions; clear cash tie-out.
* **21–16**: Forecast mostly sound; limited backtesting or weak scenario discipline.
* **15–0**: Forecast does not reconcile; no evaluation; unjustified assumptions.

5) Decision memo & communication (10 pts)
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* **10–9**: Clear actions, quantified impact ranges, risks, monitoring KPIs,
  and accountable owners.
* **8–6**: Good narrative but vague actions or limited quantification.
* **5–0**: Unclear, non-actionable, or not decision-focused.

Optional appendices (high value)
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These are optional, but they often improve clarity and reproducibility:

* **A: Excel templates** (bank rec, KPI dictionary, forecast assumptions log, 13-week cash)
* **B: QuickBooks export guide** (what to pull, how to structure)
* **C: Python quick labs** (pandas cleaning, time series baselines, regression driver model)
* **D: Common accounting-data pitfalls checklist** (timing, misclass, duplicates, reversals, one-offs)