Probability Distributions

A probability distribution is a mathematical function that describes the likelihood of obtaining the possible values for an event. A probability distribution may be either discrete or continuous. A discrete distribution is one in which the data can only take on certain values, while a continuous distribution is one in which data can take on any value within a specified range (which may be infinite).There are a variety of discrete probability distributions. The usage of discrete probability distributions depends on the properties of your data. For example, use the:

• Binomial distribution to calculate probabilities for a process where only one of two possible outcomes may occur on each trial, such as coin tosses.Hypergeometric distribution to find the probability of k successes in n draws without replacement.Poisson distribution to measure the probability that a given number of events will occur during a given time frame, such as the count of library book checkouts per hour.Geometric distribution to determine the probability that a specified number of trials will take place before the first success occurs.

Binomial Distribution

The binomial distribution is probably the most widely known of all discrete distribution. It is a type of distribution that has two possible outcomes. One typical example of using binomial distribution is flipping coins. A coin toss has only two possible outcomes: heads or tails, and each outcome has the same probability of 1/2. Let’s take a look at when the Binomial Distribution can be used!

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