Sampling Distribution Simulator
Demonstrates the Central Limit Theorem and the concept of a sampling distribution interactively.
What it does
- Adjust the population shape (normal, skewed, uniform, bimodal)
- Set the sample size (n)
- Choose the number of samples to draw
- Watch how the distribution of sample means takes shape
Key concepts illustrated
- The sampling distribution of the mean becomes approximately normal as sample size grows, regardless of the population's shape
- Larger samples produce a narrower sampling distribution (smaller standard error)
- The mean of the sampling distribution equals the population mean
This is a teaching tool — it generates illustrative data to build intuition, not to analyse your data.
A UniversalChatBot is available for discussion.