Time complexity in simple words can be described as the number of steps executed in order to reach the final output.It depends on the ram , other simultaneously running threads and so on.

The first type is **O(1)**

So it means for any number of input the output is constant single step. For example

```
n=int(input())
if(n>0)
print("Hello World")
```

Second one is **O(n)**

This means that the number of steps to get to the final result is equal to the input of the program.

```
n=4
for(int i=0;i<n;i++){
System.out.println("Hello world");
}
```

Next is **O(n^2)**

This can be calculated simply multiplying the length of the nested arrays

**O(log(n))**

Example take a binary tree for a possible of all binary representation of digits like 1 or 0... or take binary search as an example

We are dividing each time time based on the condition till we get the element we searched for So the time complexity of both these cases are logn

*Thank you or reading*

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