What are some important differences between a Normal and Binomial Distribution?
Normal distributions are more common in statistics than binomial distributions most of the time. These distributions are always symmetric and unimodal by definition.
Normal distributions can be described by their mean and standard deviation. The mean determines where the center of the distribution is located. The standard deviation determines the shape of the distribution. A larger standard deviation means a wider and flatter shape, while a smaller standard deviation means a skinnier shape.
Furthermore, unlike binomial distributions, a normal distribution is based on the values of a dataset.
An example of a normal distribution is for the heights of people in a country.
These distributions tell us the probability for a specific number of “successes” to happen, given a probability of success and number of trials.
Unlike normal distributions, binomial distributions tell us the results of only two possible outcomes: success or failure.
An example of this is flipping a coin, which can only result in heads or tails.