With the help of an example, briefly explain the dominant term in complexity.

In Big O complexity, when the number of operations of an algorithm is expressed as a sum of terms of different growth rates (e.g. $n^2 + n + 5$), the dominant term is the term that grows fastest as the input size n becomes very large - it dominates the total running time for large n, and all other (lower-order) terms and constants become insignificant in comparison and are dropped when stating the complexity. Example: For the expression $f(n) = n^2 + n + 5$, as n grows large, $n^2$ grows much faster than $n$ or the constant $5$. So $n^2$ is the dominant term, and the complexity of the algorithm is written as $O(n^2)$.