Big O notation can be generally classified as:

O(1):

Run time is independent of the input size of the problem.

O(n):

The problem requires a small amount of processing time for each element in the input. Linear.

O(n²):

The problem process all the pairs of the element. Quadratic.

O(log n):

When a big problem is solved by transforming it into a smaller size by some constant fraction. Logarithmic.

O(n log n):

When a problem is broken into smaller subproblems, solving them independently, and combining the solutions. Linearithmic.

O(2^n):

Exponential run time. To be avoided.