# What is Big O of N?

## What is Big O of N?

(definition) Definition: A theoretical measure of the execution of an algorithm, usually the time or memory needed, given the problem size n, which is usually the number of items. Informally, saying some equation f(n) = O(g(n)) means it is less than some constant multiple of g(n).

**What does Big theta mean?**

asymptotic bounds

In simple language, Big – Theta(Θ) notation specifies asymptotic bounds (both upper and lower) for a function f(n) and provides the average time complexity of an algorithm.

**What does n2 mean?**

O(n^2) means that for every insert, it takes n*n operations. i.e. 1 operation for 1 item, 4 operations for 2 items, 9 operations for 3 items. As you can see, O(n^2) algorithms become inefficient for handling large number of items. For lists O(n) is not bad for insertion, but not the quickest.

### How is Big O runtime calculated?

To calculate Big O, there are five steps you should follow:

- Break your algorithm/function into individual operations.
- Calculate the Big O of each operation.
- Add up the Big O of each operation together.
- Remove the constants.
- Find the highest order term — this will be what we consider the Big O of our algorithm/function.

**What bound Big Theta?**

Big Theta notation (Θ) : It is define as tightest bound and tightest bound is the best of all the worst case times that the algorithm can take. Let f(n) define running time of an algorithm. f(n) is said to be Θ(g(n)) if f(n) is O(g(n)) and f(n) is Ω(g(n)).

**Is big-O the worst case?**

Worst case — represented as Big O Notation or O(n) Big-O, commonly written as O, is an Asymptotic Notation for the worst case, or ceiling of growth for a given function. It provides us with an asymptotic upper bound for the growth rate of the runtime of an algorithm.

#### What is difference between N and N2?

N is an atom while N2 is a molecule of Nitrogen.

**What does o2 mean?**

oxygen

O. 2 or dioxygen, the common allotrope of the chemical element oxygen.