I was reading in "Using Maximum Likelihood Estimation" from "Econometrics for Dummies", and here's what the author had to say: "The objective of maximum likelihood (ML) estimation is to choose values for the estimated parameters (betas) that would maximize the probability of observing the Y values in the sample with the given X values. This probability is summarized in what is called the likelihood function. " (Source: http://www.dummies.com/how-to/content/using-maximum-likelihood-ml-estimation.html)
He seems to be saying that we want to find the parameters that make Y most likely to occur given an X value, but I thought the objective might be to find the parameters that most likely reveal the true P(Y|X).