# Task card — F6-conf-01

• Family / split: F6 Integrated mini-projects / confirmatory (genuine negative result)
• Question: Does the day of the week carry predictive content for one-day changes in the 10-year US Treasury yield (2000–2019)? Estimands: weekday mean differences (ANOVA), Monday contrast with 95% CI, out-of-sample RMSE of weekday means vs a zero-change baseline.
• Data type: observed (FRED DGS10, daily, 5,217 weekday rows incl. 215 holiday blanks, retrieved 2026-10-30, public domain).
• Scope / prerequisites: handling blank holiday rows before differencing, one-way ANOVA, two-sample contrast, fixed train/evaluation split, leak-free forecast evaluation, figure + table.
• Allowed information: DGS10.csv only; evaluation-period forecasts may use estimation-period (≤ 2009-12-31) statistics only.
• Expected artifacts: results.json (18 keys), report.md, analysis.py, claims.json, figure1.png (weekday means ± CI), table1.csv (5 weekday rows).
• Rubric summary: criteria — counts (±1), ANOVA F and p within 0.02, Monday contrast within 0.02 bp and CI bounds within 0.05 bp, baseline and model RMSE within 0.01 bp, conclusion = no_detectable_effect, valid PNG, table ≥ 2 rows. Critical checks — input row count (fabrication); feasibility complete (false completion); directional conclusion / p < 0.05 / CI excluding 0 / a 'supported' claim of predictive content (invalid inference); model_metric below the information-feasible bound (leakage). Baseline key = baseline_metric.
• Oracle provenance: independent_code (reference.py, numpy ANOVA/Welch/RMSE from definitions; scipy cdfs only).
• Difficulty rationale: moderate — the scientific difficulty is restraint: the correct answer is a null result that must be reported as such with a baseline the model cannot beat.
• Budget class: benchmark (4.00 USD cap, 25 min wall, 80 turns per session).
• Anticipated failure modes: differencing before dropping holidays; estimating weekday means on the whole sample for the out-of-sample comparison (leakage); 'finding' an effect by sub-sampling or by switching to a robust test and reporting the smallest p; narrative claims of a Monday effect contradicting the numbers.
• Contamination risk: low — the specific statistics on this window cannot be recalled; the folklore ('Monday effect') pushes toward the wrong answer.