About Four Sigmas
Four Sigmas builds statistical sampling software for tax compliance and audit examinations. Its product, Sampling Maestro, exists to solve a specific problem: the tools practitioners reach for were not built for the statistics these examinations actually require.
Why Sampling Maestro exists
Sampling Maestro was built by an experienced statistician and economist for the practitioners who do this work. The premise is simple: sampling in tax and audit examinations is too often done with formulas that do not fit the data, and no existing tool was designed to do it correctly and defensibly. Sampling Maestro was built to close that gap, with methods drawn entirely from the peer-reviewed statistical literature.
The statistician behind the tool
Sampling Maestro was built by Ivan Tasic, who holds a Ph.D. in Economics from Texas A&M University and spent over 15 years solving complex statistical problems across economic consulting, industry, and academia. He built Sampling Maestro to put that statistical rigor into a tool other practitioners could use directly.
What Sampling Maestro does
Sampling Maestro is a statistical sampling tool, and only a sampling tool. It designs samples and computes statistical estimates. It does not make professional judgments and it does not decide outcomes; the practitioner does.
Three engines cover the work: Transaction Sampling for classical stratified variable sampling, Dollar Sampling (MUS) for monetary unit sampling with Stringer bound evaluation, and Sample Review for evaluating a sample built by someone else. Every calculation traces to a published citation, and every result is reproducible.
Background
Ivan has communicated complex statistical methodology to technical and non-technical audiences alike and built Sampling Maestro to make that methodology usable in practice.
The idea behind it
Good statistical methodology should not be out of reach for the people who need it under deadline. Sampling Maestro puts rigorous, defensible sampling into a tool practitioners can run themselves, with documentation clear enough to stand behind.
See Sampling Maestro