Probability distributions are of two types – mainly, Discrete probability distribution and Continuous probability distribution. When probability distribution is plotted on a discrete data types then it is called as discrete probability distribution & when probability distribution is plotted on a continuous data type then it is called as continuous probability distribution. If we can represent a specific data in numerical form then it can be classified as continuous data type. If some data cannot be represented in numerical form then it is classified as discrete data type. Also discrete probability distribution tends to appear as continuous probability distribution if the data are very large.
There are a lot of terminologies and concepts which one should be aware of to understand the idea behind probability distribution. Firstly let us discuss about histogram which is an extension of a bar plot. Within bar plot each data point is represented using a bar. Histogram is a bar representation of any data based on logical grouping of bars, which are called as bins. Each bar in a histogram is called as a bin. On X-axis we plot the variable of interest and on the Y-axis we plot the frequency of occurrence of that variable. If we represent probability on the Y-axis on histogram, instead of the raw count then it is called as probability distribution.