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‫So now we're going to look at O of n squared.

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‫So I'm going to bring this back from the last video where we had one for loop after another.

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‫Except what I'm going to do is I'm going to change this where we have one for loop inside of another.

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‫And when we do this, we're going to get a very different outcome.

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‫So now let's flip over to VS code and take a look at this.

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‫So there is our new function there with our nested for loops and we will run this with the number ten.

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‫So over with our output.

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‫I'm going to scroll to the top and you can see that this starts with zero zero and then it will go all

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‫the way through to the bottom to nine nine.

10
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‫So we pass this function, the number ten, and it printed out 100 lines.

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‫So now let's flip back.

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‫So this ran n times n times or n squared, and that is where we get o of n squared.

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‫So now let's take a look at o of n squared on our graph and you can see that o of n squared grows much

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‫faster than o of n, which is to say it is a lot less efficient than o of n.

15
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‫So if you have two different ways that you could write a particular function and one way is O of n squared

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‫and the other way is O of n, that would mean that o of n is going to be the far better way to write

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‫that function.

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‫And o of n squared will be the least efficient big o that we will see in this course.

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‫And that is our overview.

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‫Of O of n squared.