The Poisson distribution provides the probability of a given number of events occurring in a fixed interval of time. This is a discrete distribution - we canโt have only half an event occurring! We also cannot have two occurrences of the phenomenon happening at exactly the same time or in exactly the same place.
Normal distributions are symmetrical. This means that 50% of values are less than the mean and 50% are greater than the mean. There is more data in the middle of the distribution than in the tails. This is a continuous distribution.
This is related to the Poisson distribution - it is the probability distribution of the time between events in a Poisson process. The exponential distribution is often concerned with the amount of time until some specific event occurs and is a continuous distribution.
For the uniform distribution, every event is equally likely to occur. Not to be confused with a constant value, which would always produce the same value. The uniform distribution has events with the same probability of occurring. It can be a continuous or discrete distribution.
This site has been created as part of my PhD thesis on perceptions of randomness. I am always keen for feedback, so please email me any thoughts you have via amy.renelle@auckland.ac.nz. Thank you to my supervisors, Dr. Stephanie Budgett and Dr. Rhys Jones, for their guidance throughout my project. I would also like to thank Anna Fergusson for her help inspiring and creating this website. You can find the references for this site here.