Hi
I think you (johnpe21) have missed the point.
In the solution, the examiner is showing that you can simplify your calculations by first computing the log likelihood for the i-th sample point. As all sample points comes from same distribution, the final result will be just the sum of the log likelihood of the i-th sample point (the sum is taken over all values of i from 1 to n). This approach will not work if the sample points come from different distributions like a mixture or some sample points are censored observations.
You will usually not be asked to derive MLE of an unknown parameter for a given data with 1 sample point ie when n =1.
PS: Given this is now so close to the exam day, I would suggest you forget this approach to the solution and only think of doing it in the usual way i.e. writing the likelihood for the whole sample. You can never go wrong if you attempt this way.
Last edited: Sep 24, 2012