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SDIST: Stata module to simulate the Central Limit Theorem


  • Marshall Taylor

    (University of Notre Dame)

Programming Language



A sound understanding of the central limit theorem is crucial for comprehending parametric inferential statistics. Despite this, undergraduate and graduate students alike often struggle with grasping how the theorem actually works and why researchers rely on its properties to draw inferences from a single unbiased random sample. This package, sdist, offers a tool for teaching and learning the central limit theorem via easy-to-generate simulations. Specifically, sdist can be used to simulate the central limit theorem by (1) generating a matrix of randomly-generated normal or non-normal variables, (2) plotting the associated empirical sampling distribution of sample means, (3) comparing the true sampling distribution standard deviation to the standard error from the first randomly-generated sample, and (4) automatically producing a side-by-side comparison of the two distributions.

Suggested Citation

  • Marshall Taylor, 2017. "SDIST: Stata module to simulate the Central Limit Theorem," Statistical Software Components S458307, Boston College Department of Economics, revised 01 Feb 2018.
  • Handle: RePEc:boc:bocode:s458307
    Note: This module should be installed from within Stata by typing "ssc install sdist". The module is made available under terms of the GPL v3 ( Windows users should not attempt to download these files with a web browser.

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