If an algorithm is of Θ(g(n)), it means that the running time of the algorithm as n (input size) gets larger is proportional to g(n).

If an algorithm is of O(g(n)), it means that the running time of the algorithm as n gets larger is **at most**proportional to g(n).

Normally, even when people talk about O(g(n)) they actually mean Θ(g(n)) but technically, there is a difference.

http://stackoverflow.com/questions/471199/what-is-the-difference-between-%CE%98n-and-on

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