Your guide to the Galton Board Simulator
Discover the fascinating world of probability with the FINIOS Galton Board Simulator. This guide will walk you through its features, helping students understand complex statistical concepts with ease and clarity. We aim to help students grasp the core ideas of probability and statistics.
Set the parameters
Begin your exploration by configuring two crucial parameters. The 'Number of Rows (n)' defines the layers of pegs the ball will pass through, influencing the distribution's smoothness. A larger 'n' yields a smoother, more bell-shaped curve, while a smaller 'n' shows discrete distributions. The 'Bias (p)' dictates the probability that the ball moves to the right at each peg. A bias of p=0.5 ensures a symmetric board, p>0.5 shifts the distribution right, and p<0.5 shifts it left. Once these values are entered, tap 'Start Simulation' to navigate to the Galton board screen.
Run and adjust the simulation
On the simulation screen, watch as balls automatically begin dropping. Each ball moves left or right at every peg according to your selected bias, with its landing position (bin index) being recorded. A histogram dynamically builds up at the bottom as more balls are dropped, illustrating the empirical distribution of landing positions. You can control the animation speed: a downward arrow helps visualise individual peg interactions and the path of each ball, while a upward arrow quickly stabilises the histogram, revealing the underlying distribution.
Interpret your findings
Observe how with small row numbers, the distribution appears discrete, while with larger row numbers, the histogram approximates a normal (bell-shaped) curve. With many balls, the histogram becomes smoother and converges to the theoretical binomial distribution, demonstrating the Law of Large Numbers. Additionally, changing the bias shifts the centre of the distribution. This simulator provides invaluable educational insight into Bernoulli trials (left/right decisions), the Binomial distribution, the Normal approximation, and the convergence of empirical frequencies. This makes complex probability concepts accessible for students, offering a clear visual representation of statistical principles.