Synthetic correlated measurements with a known covariance
Generate 256 paired synthetic measurements through a declared linear transformation of independent standard-normal draws, with known population covariance.
Proposed original example. Source release and any execution are separate steps.
Can covariance and correlation implementations be calibrated against a transparent generator?
Record the population covariance, every generated row, and finite-sample estimates; distinguish sample variability from implementation error.
What you could produce
- A scoped observations JSON record and a comparison with the stated reference.
Before you use it
- Python 3.13 standard library
Limits to keep in view
- No research code was executed by the preparation tool.
- Author output cannot issue an independent scientific-verification result.
Source and permission context
Original local preparation by the Executable Science seed collection; upstream API references remain separately attributed.
Catalog listing reviewed. This review covers the description and source links displayed here.
Local draft title, collective byline, original summary, and proposed split terms reviewed.
Reviewed 2026-09-14. Copying or adapting source files remains subject to their own terms.
Before copying source material
- Proposed local-draft licenses: original code MIT, explanations CC-BY-4.0, synthetic numeric data CC0-1.0; publication/disclosure approval remains separate.
Put this resource to work.
Test an analysis against data with known generating truth
Can the analysis distinguish finite-sample variation from leakage, missingness bias, or a covariance bug?
Open the brief RESEARCH BRIEF · 7 SOURCESDesign a generative-model calibration check
Can inference recover declared generating quantities without conflating posterior predictive fit and parameter calibration?
Open the brief RESEARCH BRIEF · 7 SOURCESPrepare controls for an interpretability claim
Does a proposed attribution or activation-based conclusion survive its stated baseline, precision and intervention controls?
Open the brief