Note that f(n) = O(g(n)) denotes an asymptotic upper bound. So it would be correct (if confusing) to say that 2n+3 = O(n^2). This is important for use in algori

Note that f(n) = O(g(n)) denotes an asymptotic upper bound. So it would be correct (if confusing) to say that 2n+3 = O(n^2). This is important for use in algorithmic complexity because we may not always be able to determine the running time even up to a constant, but can more easily infer an upper bound. Using Omega instead denotes an asymptotic lower bound. To denote both, you use Theta: f(n) = Theta(g(n)) means that for two constants 0 < c1 < c2 and large enough n, we have c1 < f(n)/g(n) < c2. Finally, little o denotes vanishing behaviour. f(n) = o(g(n)) when f(n)/g(n) goes to 0 in the limit.