I have the following excerpt in my statistics textbook:
I am confused by the sentence: "Another way statisticians treat this model is that, assume $X_1...X_n$ are random variables, we make inferences conditional on their observed values."
Aren't $X_1...X_n$ simply observations of a random variable, $X$? For example let's say I have a random variable $X$ is a persons weight and random variable $Y$ is a persons blood pressure. Then $(X_1, Y_1)$ are an observation of those RVs. How could $X_1$ be a RV?
Maybe its an RV if that specific persons weight (person associated with $X_1$) is sampled multiple times?