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Other Common Asymptotic Notations and Why Big O Trumps Them

Other Common Asymptotic Notations and Why Big O Trumps Them

Learn about the various asymptotic notations for algorithms and why computer scientists prefer Big O over other notations.

Big Omega: Ω(.)\Omega(.)

Mathematically, a function f(n)f(n) is in Ω(g(n))\Omega(g(n)) if there exists a real constant c>0c > 0 and there exists no>0n_o > 0 such that f(n)cg(n)f(n) \geq cg(n) for nnon \geq n_o. In other words, for sufficiently large values of nn, f(n)f(n) will grow at least as fast as g(n)g(n).

Note: It is a common misconception that Big O characterizes the worst-case running time while Big Omega characterizes the best-case running time of an algorithm. There is no one-to-one relationship between any of the cases and the asymptotic notations.

The following graph shows an example of functions f(n)f(n) and g(n)g(n) that have a Big Omega relationship:

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Big Omega
Big Omega

Quick quiz on Big Omega!

1

(True or False) n3Ω(1)n^3 \in \Omega(1).

A)

True

B)

False

Question 1 of 30 attempted

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