AI & Machine Learning · reviewed in August 2026
Probability
Probability measures, between 0 and 1, how likely an uncertain event is to happen. In data science and machine learning it's the underlying mathematical language for modeling uncertainty — from the probability a classification model assigns to each class, to the statistical tests that decide whether a result is significant.
Frequently asked questions
What is a probability distribution?
It's a description of how likely each possible value of a random variable is — for example, the normal distribution describes many natural phenomena with a bell shape centered on the mean.
What's the difference between probability and statistics?
Probability starts from a known model and predicts what data it might produce; statistics runs the reverse path, starting from observed data to infer what model or parameters likely generated it.
Why does a classification model output 'probabilities' instead of just a label?
Because giving the model's confidence (for example, 87% probability of spam) enables more informed decisions than a binary label — like setting a different threshold depending on the cost of being wrong.