Explain Big-Oh analysis.

What are some limitations on Big-Oh analysis?

Why is algorithm analysis important?

If Algorithm "A" is O(n) and Algorithm "B" is O(n), which is the
preferred algorithm?

If Algorithm "A" is O(n) and Algorithm "B" is O(n^2), which is the
preferred algorithm?


If Algorithm "A" is O(n) and Algorithm "B" is O(n^2), is Algorithm "A"
gauranteed to be faster for all n? Explain.

When given a choice between O(n) and O(log n) algorithms, which is
preferred?


Explain (bubble|selection|quick) sort.

Which sorting method of the three we have learned is preferred?

What is the Big-Oh analysis of each sort in the worst case?
   -Each have O(n^2) in the worst case.

What is the Big-Oh analysis of each sort in the average case?
   -Bubble and selection have O(n^2) in the average case.
   -Quicksort has O(n log n) in the average case.


-Quick sort has better average performance - why? What advantage does
 it have over the other methods?