Central Limit Theorem for exponential distribution Suppose that $X_1,\ldots,X_n$ are a random sample from a population having an exponential
distribution with rate parameter $\lambda$.
Use the Central Limit Theorem to show that, for large $n,$ $\sqrt{n}(\lambda\bar{x}-1) \sim \operatorname{Normal}(0,1)$
My attempt: honestly I am really not understanding what this question is asking. I can see that for an exponential distribution, it would have to be shifted by $\lambda$ and scale by a factor of $\sigma$?

Hint: express $\sqrt{n}(\lambda \overline{x} - 1)$ in terms of the sum of the random variables.  What does the Central Limit Theorem say about this sum?
