Fixed some typos

I didn't like the wording in some parts.

There are more substantial changes that would want to make but don't want to mess up the voice of the document.

Namely:

1) Highlight MCMC is just a means of performing  Bayesian Inference. There are other algorithms for doing it that are beyond the scope of the book.

2) MCMC roughly moves towards regions of high probability, but the goal is not to find the Maximum A-Posterior point. MH moves are designed so as to make sure our samples are still from the target distribution.

3) The mixture models example will have an exponential number of peaks, but because they are all isomorphic to each other, sampling around any of them is not a big deal.

I am including this here more to clarify how much detail do you believe is appropriate for this book.