The central limit theorem has an assumption like this "Let {X1, …, Xn} be a random sample of size n — that is, a sequence of independent and identically distributed random variables drawn from distributions of expected values given by µ and finite variances given by σ^2." (quoted from wikipedia)
But in my understanding, a random variable should be something like "the Grade of a student" which can take on some values. "A sequence of random variables" is more like a random variable that takes on a sequence of values. e.g. Given a sequence of observations of Grade where Grade is one random variable.
So how do I make sense of this sequence of independent and identically distributed random variables.
Thank you so much for help!
Consider, for example, an infinite sequence of coin-tosses with a fair coin.
$X_n = 0$ or $1$ depending on whether the $n$'th toss results in heads or tails.