Type II Error Rate (Beta) from Power Calculator
Calculates type II error rate β = 1 − power, type I error rate α, and the four outcomes of a hypothesis test with their...
Probability, sampling, and descriptive statistics made readable.
Means, medians, standard deviations, confidence intervals, and sample size planning — with formulas and worked examples for each tool.
Calculates type II error rate β = 1 − power, type I error rate α, and the four outcomes of a hypothesis test with their...
Calculates the Erlang B formula for call blocking probability and Erlang C for probability of queuing in a M/M/c telepho...
Calculates probability mass, mean μ = (a+b)/2, variance σ² = (n²−1)/12, and P(X ≤ k) for a discrete uniform distribution...
Calculates the total probability of event B using the law of total probability: P(B) = P(B|A₁)·P(A₁) + P(B|A₂)·P(A₂) + P...
Applies Chebyshev's inequality to give a distribution-free bound on the probability of a value lying more than k standar...
Calculates odds ratio OR = (a·d)/(b·c) and relative risk RR = (a/(a+b)) / (c/(c+d)) from a 2×2 exposure/outcome continge...
Applies Bayes' theorem to update a prior probability with new evidence, outputting the posterior probability and likelih...
Calculates the log-normal mean E[X] = exp(μ+σ²/2), median exp(μ), mode exp(μ−σ²), and variance (e^(σ²)−1)·e^(2μ+σ²) from...
Calculates the expected value (mean) and variance of a discrete probability distribution from up to six outcome-probabil...
Applies Bayes' theorem: P(H|E) = P(E|H)·P(H) / [P(E|H)·P(H) + P(E|¬H)·P(¬H)]. Used in medical testing, spam filtering, a...
Applies the Cantelli inequality: P(X − μ ≥ kσ) ≤ 1/(1+k²), a tighter one-sided bound than Chebyshev. Also computes the t...