Standard distribution types
Standard types of distribution are the normal distribution, binomial distributions and exponential distributions. Normal and binomial distributions deal with discrete data whereas exponential deals with continuous data.
A variable graphically described with a bell-shaped density curve.
Binomial experiments involve only two choices and their distributions involve a discrete number of trials of these two outcomes. For example, the flipping of a coin. Therefore a binomial distribution is a probability distribution of the successful trials in the experiment.
When a data set is clustered around two different modes, it is described as being bimodal.
Exponential distributions deal with continuous data on a scale e.g. you may measure travel times between places by a scale of minutes.
A type of probability distribution that resembles the normal distribution but differs slightly with its additional parameter known as “degrees of freedom”. How the distribution compares to the normal curve depends on how close the mean is to 0 and the standard deviation to 1.
A probability distribution which analyses the probability of multiple outcomes occurring in a given timeframe.
Example: The probabilities of the likely number of goals in a football match, based on averages taken from recent results.
A table listing all categories (or classes) and their frequencies.
The percentage of the frequency of a class against the overall frequency of the sample.
Relative frequency distribution
A table listing all classes and their relative frequencies, the total of which will equal 1 (100%).