1.4, due on September 13

What interested me the most in the reading was learning about different algorithms used to solve the same problem. I had seen this happen before with things like merge and sort algorithms, but never with linear algebra applications. I'd like to actually understand how those algorithms work so I can see why they work better.

What was the most difficult to understand was the explanation of methods to solve linear systems using matrix equations of the form Ax=b. The LU decomposition method isn't familiar to me and the explanation wasn't detailed enough for me to grasp why that would be faster than trying to find the inverse. Was I supposed to understand why solving Ly=b and Ux=y would each cost ~n^2, or just take that on faith?

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