databutler-stats
Exact statistics & probability: distributions, hypothesis tests, CIs, Bayesian updates, regression.
Community: Submitted by a user or imported; check the owner before granting accessOnlineNo sign-inGlobalFreeCan modify data
What it can do
What data it sees
Do you need an account
No: the server works without sign-in
Exact statistics & probability: distributions, hypothesis tests, CIs, Bayesian updates, regression.
Server tool list (6)
Raw names from tools/list. Only developers need these.
| descriptive_stats | Summary statistics for a numeric array: mean, median, sd, variance, quartiles, IQR, skewness, min/max. |
| distribution | Evaluate a probability distribution (normal, t, chi2, binomial, poisson): pdf/pmf and cdf at a value, and/or the quantile at a probability, plus mean & variance. Params per dist: normal {mean,sd}, t {df}, chi2 {df}, binomial {n,p}, poisson {lambda}. |
| hypothesis_test | Run a significance test and get the statistic, p-value, and a plain-language interpretation with assumptions. test = one-sample-t {data, mu0}, two-sample-t {data1, data2}, one-proportion-z {successes, n, p0}, two-proportion-z {successes1,n1,successes2,n2}, chi2-gof {observed, expected?}, chi2-independence {table}. Optional tail: two-sided (default) | greater | less; alpha default 0.05. |
| confidence_interval | Confidence interval for a mean (t-based; from data, or n/mean/sd) or a proportion (Wilson; successes/n). kind = mean | proportion; confidence default 0.95. |
| bayes_update | Discrete Bayesian update: given competing hypotheses each with a prior and the likelihood of the observed evidence, return normalised posteriors. Priors are renormalised to sum to 1. |
| linear_regression | Simple linear regression of y on x: slope, intercept, r, r², slope std error and p-value, equation. |