# Big O

What is Big O?

Big O is a way to measure the time and space of the algoritm corespoinding the input they are given.

**Important concepts**

- growth is with respect to the input
- Constants are dropped ( ignore constant )
- Worst case is usually the way we measure

Example :

So when someone says Oh of N, they mean your algorithm will grow linearily based on input.

- O(N)
- O(N^2)
- O(LOG N)
- O(N LOG N)

Trick

If the input halves at each step, its likely O(LogN) or O(NlogN)

**Why do we use it?**
Often it will help us make decisions about what data structures and algorithms to use. Knowing how they will perform can greatly help create the best possible program out there.

**Resource**: