## CS101: Big-O and How it’s Relevant

Big-O is a way of expressing time and space complexity of an algorithm. Complexity is the rate of growth given variable inputs. Complexity is implicitly expressed in worst-case unless otherwise stated.

For example:

```
function printArray(n) {
for(var i = 0; i < n.length; i++) {
console.log(n[i])
}
}
```

`printArray`

in this instance is `O(n)`

time complexity and `O(1)`

space complexity.