1. The problem is to understand the meaning of "iid" in probability and statistics. 2. "iid" stands for "independent and identically distributed". This means that a set of random variables all have the same probability distribution and are mutually independent. 3. Independence means the occurrence of one event does not affect the probability of another. 4. Identically distributed means each variable follows the same probability distribution with the same parameters. 5. This concept is fundamental in many statistical methods and theorems, such as the Law of Large Numbers and the Central Limit Theorem. 6. For example, if $X_1, X_2, \ldots, X_n$ are iid random variables, then for any $i \neq j$, $P(X_i \cap X_j) = P(X_i)P(X_j)$ and each $X_i$ has the same distribution function $F(x)$.