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- W4240764369 abstract "Understanding 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 works and why researchers rely on its properties to draw inferences from a single unbiased random sample. In this paper, I outline a new Stata package, sdist, which can be used to simulate the central limit theorem by generating a matrix of randomly generated normal or non-normal variables and comparing the true sampling distribution standard deviation to the standard error from the first randomly-generated sample. The user also has the option of plotting the empirical sampling distribution of sample means, the first random variable distribution, and a stacked visualization of the two distributions." @default.
- W4240764369 created "2022-05-12" @default.
- W4240764369 creator A5083384606 @default.
- W4240764369 date "2018-03-23" @default.
- W4240764369 modified "2023-09-24" @default.
- W4240764369 title "Simulating the Central Limit Theorem" @default.
- W4240764369 doi "https://doi.org/10.31219/osf.io/chty3" @default.
- W4240764369 hasPublicationYear "2018" @default.
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