A coin toss is simple. A thousand coin tosses become a small laboratory for understanding uncertainty.
Sample post · Created to preview Models & Musings.
If a coin is fair, heads and tails each have probability one-half. That does not mean every sequence will divide neatly down the middle. Ten tosses can look surprisingly lopsided.
Let chance do the work
A simulation repeats a simple random experiment many times. Instead of asking for one perfect prediction, we collect a range of possible outcomes. Plotting the number of heads across repeated runs makes that range visible.
As the number of independent tosses grows, the proportion of heads tends to settle closer to one-half. The total difference between heads and tails can still grow. Proportions and counts tell different stories.
This is a starting point for Monte Carlo thinking: specify a model, repeat it, and inspect the distribution. The simulation reflects the assumptions we put in, so the most useful question is often whether those assumptions fit the situation.
Leave a Reply