All tools
Probability Simulator
Run dice, coins, cards, spinners, and custom distributions through Monte Carlo simulation and watch the results converge on the theoretical probability.
Experiment
Run a trial to see the outcome here.
Simulation
0 / 200 trials
Histogram — experimental vs theoretical
Running probability — Law of Large Numbers
x = 100, y = 0.1667
Statistics
Mean
— experimental
3.5 theoretical
Variance
— experimental
2.917 theoretical
Standard deviation
— experimental
1.708 theoretical
Trials
0 experimental
— theoretical
Frequency table
| Outcome | Count | Experimental | Theoretical |
|---|---|---|---|
| 1 | 0 | — | 0.167 |
| 2 | 0 | — | 0.167 |
| 3 | 0 | — | 0.167 |
| 4 | 0 | — | 0.167 |
| 5 | 0 | — | 0.167 |
| 6 | 0 | — | 0.167 |
Central Limit Theorem
Draws 300 independent samples of 5trials each from the current experiment, averages each sample, and histograms the resulting sample means — the distribution should look progressively more bell-shaped (normal) as the sample size grows, even though the experiment’s own distribution usually isn’t.