Out of 5 rolls, out of 5 flips.

Does the probability of every given proportion, for example, one head out of 100 flips, 10 heads out of 100 flips or 1500 heads out of a billion flips becomes small.

So he unties Odysseus, and Odysseus flips out.

It flips backwards.

I'll number the flips.

So it's essentially, there are going to be out of six flips,

P of flips because that's the only way you can get the flips.

This is my flips column.

This sign flips that around.

But when you fold it that way again, it, like, flips inside out.

Where you get out of the six flips, you're essentially choosing four heads.

Multiple flips, a little more time.

Now. Let's go to 5 coin flips.

But if I have 8 flips there's 56 ways of picking 3 of those flips to be heads.

Specify the amount of time between card flips

Together they are equal to P of flips.

And another chap flips his wings! All right.

This is equal to 1 minus the probability of getting exactly one heads out of 5 flips.

It could be any 1 of those 5 flips.

Let's give a name to each of our flips.

And we're essentially saying, out of the 32 outcomes, 5 satisfy the event that we're looking for exactly 1 heads out of 5 flips.

And you can see, eventually the airport actually flips directions.

And what this theorem really is about many coin flips.

This is going to close down. This arrow flips around.

And the way you could think of it is we're going to do 5 flips, exactly 1 of the flips is going to be heads.

So similarly, if I'm just picking flips and I have to say, OK, 3 of these flips are going to get into the heads car.

Let me ask you again. Suppose you make 111 coin flips.

So we talked about coin flips, and we flipped some coins.

Suppose I care about 90 confidence and from my coin flips,

As a result it could really happen that this thing flips.

Andrew flips them around and inserts them back in the body

I'm choosing which of the flips get selected, so to speak.

That's the probability of exactly 9 heads out of 12 coin flips for this heavily loaded coin that mostly gives you heads.

The probability of out of the seven flips of not getting any heads, that is equal what has to be true then?

So let's ask an easy quiz. Suppose we do 2 coin flips.

Perhaps the picture completely flips if you are low on socioeconomic status.

So depending on where it looks, it flips between the two possibilities.

So it kind of flips things on its head a little bit.

And then essentially we would multiply 2 times the number of flips.

So let me make a little column, we'll call these the flips.

So there's a little bit better than 1 in 5 chance that I get exactly 3 out of the 8 flips as heads.

The way she flips her ponytail will charm you before you realise it.

These are the empirical means for these sequences of a 1000 coin flips.

So probability is a method of describing the anticipated outcome of these coin flips.

It applies to coin flips and many of the other examples we discussed before.