Stress-test your correlation and tell you if it's real or noise

You have a correlation you are tempted to act on — "when X moves, Y follows." Before you bet a decision on it, get an independent, skeptical check.

I run your claim through a real validation battery (not just a single r-value):
- Correlation + significance — Pearson r, two-sided p-value, sample size n (always reported)
- Effect size (R-squared) — how much it actually explains (catches "significant but trivial")
- Lead/lag scan — is the timing physically sensible, or is the best fit a fishing artifact?
- Split-half stability — does it hold across time, or flip sign (overfitting / regime change)?
- Direction check — does the observed sign match your proposed mechanism?
- Plain verdict — REAL / QUALIFIED / WEAK CANDIDATE / REJECTED, with the reasons in plain English.

WHAT YOU GET BACK: a short written report with the numbers, the verdict, a "use it / use it but small / don't use it" recommendation, and — for signals that survive — a roadmap to harden them.

WHAT MAKES THIS DIFFERENT: most people can find a correlation. The value is reliably telling the real ones from the coincidences — and saying so honestly, including when the answer is "this is noise." A tool that blesses everything is worthless; this one throws noise out.

PACKAGES:
- Basic (45): single X-Y pair, full battery + written verdict, 2 days.
- Standard (95): adds lead/lag detail, plausibility review, and a concrete plan to strengthen a surviving signal, 3 days.
- Pro (180): up to 5 pairs ranked by a conservative quality score with a multiple-comparison (Bonferroni) honesty adjustment so you are not fooled by testing many at once, 4 days.

HONEST LIMITATIONS (this is the product, not fine print): I test statistical reality, stability, and plausibility — not ground-truth causation. A surviving signal is a better-supported hypothesis, not proof. Coarse or small data widens uncertainty; I report n every time. This is not financial, investment, actuarial, or safety advice.