Answer to Question #209944 in Statistics and Probability for Ahmed Ali

Question

Briefly explain the following topics with the help of example.

• Discrete Probability
• Continuous Probability
• Normal Distribution
• Hypergeometric Distribution
• Poisson Distribution

Answer 1

Discrete probability

This is the probability that Counts events with a finite or countable consequence. Example is Bernoulli probability distributions.

Continuous Probability

This is the probability where the outcomes can be found anywhere on a continuum. Example is Temperature on a given day or month.

Normal Distribution

This is a function that depicts the distribution of a large number of randomly generated variables. Example is a symmetrical bell-shaped graph.

Hypergeometric Distribution

The hypergeometric distribution is a discrete probability distribution that defines the probability of k successes in n draws without replacement from a limited population of size N containing exactly K items with that feature, where each draw is either successful or unsuccessful. Example: A deck of cards contains 20 cards: 6 red cards and 14 black cards. 5 cards are drawn randomly without replacement. What is the probability that exactly 4 red cards are drawn?

Poisson Distribution

This is a discrete frequency distribution that expresses the likelihood of a set of independent occurrences occurring at a specific moment. Example: If the average number of people who rent movies on a Friday night at a single video store location is 400, a Poisson distribution can answer such questions as, "What is the probability that more than 600 people will rent movies?".