XLSTAT - Distribution Sampling

Why do we use sampling distribution?

From a dataset it may be useful to select a fewer amount of individuals to be submitted to further analysis. This can be use for validation purposes or to shorten the computation time.

Assuming you know the dataset distribution you could select a smaller set following the same distribution to run your analyses and tests. XLSTAT distibution sampling tool enables you to do just that.

XLSTAT distribution sampling tool

This module generates random data based on a theoretical or empirical distribution. For a theoretical distribution, you must choose the probability distribution and define its parameters. For an empirical distribution, you must select a column with quantitative reference data.

XLSTAT provides the following distributions:

• Arcsine
• Bernoulli
• Beta (2 options)
• Binomial
• Negative binomial type I and II
• Chi-square
• Erlang
• Exponential
• Fisher
• Fisher-Tippett
• Gamma
• GEV (Generalized Extreme Values)
• Gumbel
• Logistic
• Lognormal (2 options)
• Normal
• Standard normal
• Pareto
• PERT
• Poisson
• Student
• Trapezoidal
• Triangular
• Uniform and Uniform discrete
• Weibull (3 options