Probability Function

In Data Science, a probability function is a mathematical function that maps an event to its probability of occurrence. It is a fundamental concept in probability theory and is used extensively in statistical inference, machine learning, and data analysis. A probability function can be either discrete or continuous. A discrete probability function is used when the event can take on only a finite or countably infinite number of values, while a continuous probability function is used when the event can take on any value within a certain range. The most common examples of probability functions are the probability mass function (PMF) and the probability density function (PDF). The PMF is used for discrete random variables, while the PDF is used for continuous random variables. Probability functions are essential in modeling and analyzing data, as they allow us to make predictions and draw conclusions based on the likelihood of certain events occurring.
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