io.github.physics-star-cat/databutler-stats

databutler-stats

Exact statistics & probability: distributions, hypothesis tests, CIs, Bayesian updates, regression.

1.0.0
Version
remote
Transport
6
Tools

Security review

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Reviewed Jan 1, 2000.

  • tools: 6 tools scanned
  • metadata: scanned

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Tools (6)

  • 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.