Uncensored AI for biostatistics
Which test, why that one, and what the output is actually saying
The statistics in biology papers are mostly the same five tests applied badly. Learning which test, and what the output sentence must say, is a small body of knowledge that pays for the whole degree.
Why the mainstream APIs fail here
The stats help online is either aimed at statisticians or wrong. A general chatbot hedges on anything touching epidemiology or clinical risk, which is the data half the life sciences actually have, so people guess at the test and report the p-value as the finding.
How Wild West API is used for this
Describe the design and the data; ask which test fits and what its assumptions need from your data. Paste the output; ask for the results paragraph in journal register, including the confidence interval. Ask what the result does not show; that sentence keeps reviewers calm.
A working loop
- Design first, test second; most wrong tests are wrong at the design step.
- Paste the actual output, not your memory of it.
- Write the limitation sentence yourself; you know which one it is.
Details are on the privacy page. Per-model prices are on /models and the pricing model is on /pricing.