# IID random sample assumption in classical OLS regression

In classical OLS regression, I get that the assumptions:

• Strictly exogenous errors $$\implies$$ unbiased OLS estimator
• Errors are normally distributed $$\implies$$ allow to make tests (t-tests, etc.)

But what is the use of the i.i.d. random sample in the classical OLS regression? What can it allow us to do that before we couldn’t do?