Probability distributions

Try it step by step

1. Define a distribution such as .
2. Use its pdf, cdf or inversecdf method for the question you want to answer.
3. Use mean or stdev to inspect its parameters.
4. Use random(count,seed) to draw a repeatable sample.

Examples to try

Each card is one input. For definitions, enter the cards in order. Formula-only cards belong in the tool described above.

Options explained

Available distributions

normaldist, uniformdist, tdist, chisqdist, binomialdist, poissondist, exponentialdist and geodist. Each checks its parameter domain.

pdf(x)

Density for a continuous distribution or probability mass for a discrete one. A continuous density value is not itself an interval probability.

cdf(x) / cdf(lower,upper)

Cumulative probability or probability over a supported interval.

inversecdf(p)

Finds a quantile for a probability between 0 and 1.

mean() / stdev()

Returns a supported distribution summary.

random(count,seed)

Draws samples; supply a fixed seed to reproduce them. Distribution sampling has its own count limit of 1,000.

Display

Discrete distribution plots show at most 1,000 integers near the mean.