Central Limit Theorem Explorer

Watch sample means converge to a normal distribution

The Central Limit Theorem states that regardless of a population's distribution shape, the distribution of sample means approaches a normal distribution as sample size increases. Adjust the controls and watch the magic happen in real time.

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Controls

1. Population Distribution

2. Sample Size (n)

n = 5

3. Draw Samples

📚 Teaching Tip

Start with a skewed or bimodal population to make the CLT effect most dramatic. Increase sample size to n ≥ 30 and watch the sample means form a beautiful bell curve!

Population Distribution N = 10,000

Distribution of Sample Means 0 samples

Samples

Mean of Means

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Std Error

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No samples drawn yet. Click a button to begin!

🎯 Key Insight

Use This Demo in Your Teaching

This interactive demo is self-contained and can be embedded directly into your LMS (like Blackboard) or downloaded for offline use. No coding required.

Tip: In Blackboard, create a new Item, switch to HTML view, and paste the code. The demo will work directly in students' browsers with no additional setup needed.