Distribution Visualizer
Overview
The Distribution Visualizer provides interactive exploration of five common probability distributions: Normal, Binomial, Poisson, Uniform, and Exponential. Adjust parameters with sliders and watch the distribution shape change in real-time, making it perfect for learning statistics, selecting appropriate distributions for modeling, and understanding how parameters affect distribution characteristics.
Tips
- Change one parameter at a time to isolate its effect on the distribution shape
- Use the Normal distribution with mean=0 and varying standard deviations to understand spread versus peak height
- For the Binomial distribution, set p=0.5 to see perfect symmetry, then adjust to see skewness develop
- Watch how the Poisson distribution becomes more symmetric as lambda increases - it approximates Normal for large lambda values
- The Exponential distribution’s memoryless property means the probability of an event doesn’t depend on how much time has already passed
- Compare similar distributions (e.g., high-n Binomial vs Normal, or high-lambda Poisson vs Normal) to understand convergence behavior
- Use the automatic statistics display to verify theoretical properties like how Poisson mean equals its variance