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‫So with Big O, we have a few rules for simplification and the first one of those is called drop constants.

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‫So to explain this, I'm going to start with the function that we looked at in the last video, which

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‫was O of N, except that I'm going to add a second for loop and both of these are going to run in times.

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

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‫So there is our new function with our two four loops, and then we will run this with the number ten

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‫and these two for loops have printed out zero through nine here and then zero through nine here.

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‫So we pass this function, the number ten, and it printed out 20 items.

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‫So now let's flip back.

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‫So this function ran in plus in times or two in.

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‫So you might think that we're going to write this as O of two n, but we don't.

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‫We will always drop the constant and just call it O of n.

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‫So it doesn't matter if it's two N or 100 n.

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‫We're going to drop the constant.

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‫And you might wonder, why would we do that?

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‫Isn't it different to have something run two in times versus one in time?

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‫So the thing we're trying to do with Big O is figure out the broad category that the growth rate is

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‫in.

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‫So even at 100 N, it is growing linearly and that is very different than something that is say growing

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‫exponentially as in becomes very large.

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‫That exponential growth rate is in a completely different category.

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‫So that's why we have these rules of simplification.

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‫And we'll see a couple more rules of simplification as we are going through this big O section and it

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‫actually makes big O a lot easier.

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‫But our first rule of simplification.

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‫Is drop, Constance.