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Goal(s): Learn about the Central Limit Theorem: As sample size increases, the shape of the Distribution of Sample Means approaches normality (i.e., a bell-shaped curve), for any shaped population.
How: Determine both the parent population shape and the sample size.
Site: P2L.io
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The Central Limit Theorem (CLT). The Central Limit Theorem states that as the sample size increases, the shape of the Distribution of Sample Means approaches normality (i.e., a bell-shaped curve).
Additionally, as the sample size increases, the Distribution of Sample Means becomes narrower.
Options. Explore changing the parent population shape (normal, skewed, bi-modal, uniform) and the sample size (from 1 - 200).
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This HTML applet was co-developed with ChatGPT 5 through a guided iterative development process.
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