Simulate CLT
Adjust dice probabilities and see the Normal distribution emerge.
Dice face configuration (%):
Number of throws in one trial:
Z-value to mark:
Run Simulation (1000 trials)
$\mu$:
3.50
, $\sigma$:
1.71
$\bar{X} = \frac{1}{n}\sum x_i = $
0.000
$SE_{practice} = \sqrt{\frac{\sum(x_i - \bar{x})^2}{n-1}} = $
0.000
$SE_{theory} = \frac{\sigma}{\sqrt{n}} = $
0.000
$$\bar{X} \sim N\left(\mu, \frac{\sigma^2}{n}\right) \text{ when } n \to \infty$$