Probability distribution

Definition

Probability distribution is a statistical function that describes the likelihood of different outcomes in an experiment. It assigns a probability to each possible value or range of values for a random variable.

5 Must Know Facts For Your Next Test

1. Probability distributions can be discrete or continuous, depending on whether the random variable takes on specific values or any value within a range.
2. The total area under the curve of a probability distribution is always equal to 1.
3. Expected value (mean) and variance are key characteristics of probability distributions used in financial analysis.
4. Common types of probability distributions include normal, binomial, and Poisson distributions.
5. Risk management in finance often relies on understanding probability distributions to assess potential losses.

Review Questions

• What is the difference between discrete and continuous probability distributions?
• Why must the total area under a probability distribution curve equal 1?
• How do financial analysts use expected value and variance in probability distributions?

Related terms

Random Variable: A variable whose possible values are numerical outcomes of a random phenomenon.

Expected Value: The mean or average value that a random variable takes on, weighted by probabilities.

Variance:

A measure of how much values in a data set differ from the mean, used to assess volatility.