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by Scea91
3695 days ago
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Actually we don't use it informally as big-Theta, because big-Theta assumes that the lower and upper bound are asymptotically the same. For example Quicksort is O(n^2) but Omega(nlogn) it is neither Theta(nlogn) nor Theta(n^2). You probably meant that informally we just assume that the stated bound is as tight as possible. |
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No, this is flat out wrong. Big O is an upper bound on an asymptotic growth rate. Big Omega is a lower bound on the asymptotic growth rate. Big Theta is a tight bound on the asymptotic growth rate. These are independent to the average case, best case, or worst case run time of a given algorithm.
Quicksort has an average run time of Theta(n lg n). Equivalently, its average run time is O(n lg n) and Omega(n lg n). It has a worst case run time of Theta(n^2). Equivalently, its worst case run time is O(n^2) and Omega(n^2).
> Actually we don't use it informally as big-Theta,
Wrong again.