What Is the Law of Large Numbers?
The law of large numbers is a fundamental theorem of probability: as a random experiment is repeated more times, the observed frequency of any outcome converges toward its true probability. For a fair digit lottery (0–9), each digit should appear about 10% of the time in the long run.
How the Visualizer Works
Select individual US states and watch their combined digit distribution update in real time. With one state and a limited draw history, you will see bars deviating from the 10% reference line. As you add more states (more data), those deviations shrink and the distribution converges toward uniform.
Reading the Chart
The blue dashed line at 10% represents the expected frequency for each digit under a fair random process. Bar colors indicate deviation:
- Green: Within 0.5% of expected — essentially random
- Amber: 0.5–1% deviation — mild variance
- Red: More than 1% deviation — notable variance (common with small samples)
What This Tells You
When you add a single state with one year of data, you might see 8% for digit 3 and 12% for digit 7. That looks significant — but add 10 states worth of data and those extremes smooth out. Add all states and the distribution becomes nearly flat. This is the law of large numbers working exactly as expected.
The takeaway: perceived "hot" and "cold" digits at the individual state level are largely statistical noise. The more data you aggregate, the more clearly random the process becomes.
For educational and informational purposes only. Past results do not predict future draws. Play responsibly.