Asymptotic notations are notations used to describe the behaviors of the running time of an algorithm. There are three main notations, namely Big-O, Omega, and Theta.

Big-O notation, or O(running time), represents the upper bound. Omega notation, or Ω(running time), represents the lower bound. Theta notation, or Θ(running time), represents the average value or range.

Suppose n is the input size(like a list of n numbers). Also, suppose c is some positive constant (like 1, 24, 4.5, 8, and so on). Then O(n) means that the algorithm you are analyzing takes no more than c*n operations, Ω(n) means that the algorithm you are analyzing takes at least c*n operations. Θ(n) means that the algorithm is both O(n) and Ω(n), meaning it is exactly c*n operations.

As you can see here, the constants are ignored in asymptotic notations. We will get to why in the next section.