# Data audit (P1)

• File: data/schools.csv, SHA-256 0f1d8378fff2f0898762feaa08dd94d9ad04156dad6330572d98997c9005c88a (matches bundle.json)
• 1000 rows × 4 cols: school_id int (100–139), student_id int (1–1000, unique), treated int {0,1}, score float (points; 35.72–64.17, mean 50.80, sd 4.48)
• Missing values: none. Duplicate rows / duplicate student_id: 0.
• 40 schools × 25 students each (balanced); treated constant within every school; 20 treated, 20 control schools.
• No dates (no chronology). No anomalies detected; no extreme outliers (range ≈ mean ± 3.4 sd).
• Information availability: only input is the allowed file; no violation.
• Exclusions: 4 rule checks, 0 rows removed (out/exclusions.csv); n_analysed = 1000.