P(X > 3)
We can see that it becomes easier for us to calculate different outcomes without writing a lot of text. There are two types of random variables - discrete random variables and continuous random variables.
Discrete and Continuous Distributions
Discrete random variables are those random variables that can take on only a specific set of limited values which are all distinct. They are usually countable as they have a finite number of possible values. An example of discrete random variables are the outcomes from a dice. There is only a small set of values that a dice can produce, this makes it countable.
A discrete probability distribution is one that describes the probability associated with discrete random variables. That is it gives the probability of occurrence of discrete outcomes. The probability distribution of a discrete random variable is sometimes called the probability function or the probability mass function.
It would be observed from the above plot of a discrete probability distribution, that the probability of occurrence of a particular value of a random value is non-zero since the range of possibilities is finite. The type of plot above is known as a probability histogram. Examples of discrete probability distributions are binomial, poisson, hypergeometric etc.