Fill in the blank. In probability, \( a(n) \) is probability, \( a(n) ~ i s ~ a n y ~ p r o c e s s ~ t h a t ~ c a n ~ b e ~ r e p e a t e d ~ i n ~ w h i c h ~ t h e ~ r e s u l t s ~ a r e ~ u n c e r t a i n . ~ \)

In probability, \( a(n) \) is probability, \( a(n) \) is any process that can be repeated in which the results are uncertain. This concept is at the heart of probability theory, where we often deal with random experiments such as flipping a coin or rolling a die. These experiments illustrate how multiple trials can lead to varied outcomes, enabling us to quantify uncertainty and predict likelihoods. A classic real-world application of this idea is in weather forecasting. Meteorologists use probabilistic models to predict weather conditions, weighing past data against current observations. Just like flipping a coin, predicting rain involves uncertainty; while they can say there's a 70% chance of rain, there's still the possibility of a sunny day. So, next time you check the weather, remember it’s all about those probabilities!