Statistics

" In statistics, a probability density function (PDF) is a mathematical function that describes the likelihood of a continuous random variable taking on a particular value within a given range. In other words, it provides the probability distribution of a continuous random variable.

Here are some key points about probability density functions:

Continuous Random Variables: Probability density functions are primarily used for continuous random variables, which can take on an infinite number of values within a certain range. Examples of continuous random variables include the height of individuals, the time it takes for an event to occur, or the temperature at a specific location.

Probability Density: Unlike discrete probability distributions, where you can assign a probability to each possible outcome, in a continuous distribution, you assign probabilities to intervals or ranges of values. The probability density function measures the relative likelihood of a random variable falling within a particular interval.

Non-Negative and Integrates to 1: A valid probability density function must be non-negative (i.e., it cannot take on negative values) and must integrate to 1 over the entire range of possible values. This ensures that the total probability of all possible outcomes is equal to 1."