Is time complexity O(n^2) or O (n(logn)^2) better?
I know that when we simplify it, it becomes
O(n) vs O((logn)^2)
and logn < n, but what about logn^2?
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n is only less than (log n)2 for values of n less than 0.49…
So in general (log n)2 is better for large n…
But since these O(something)-notations always leave out constant factors, in your case it might not be possible to say for sure which algorithm is better…
Here’s a graph:
(The blue line is n and the green line is (log n)2)
Notice, how the difference for small values of n isn’t so big and might easily be dwarfed by the constant factors not included in the Big-O notation.
But for large n, (log n)2 wins hands down: