Machine Learning Theory - Part 2: Generalization Bounds • /r/MachineLearning

What does "drawn from the same probability distribution" mean? If you have N random variables X_1, X_2, ..., X_N, and they're "identically distributed", does that mean they're all drawn from a Gaussian probability distribution with mean \mu and variance sigma2 (for example), or does it mean that they're all drawn from a Gaussian (as an example), each with its own mean and variance?