Let me do this once again.

This time around, we have a bag, and in the bag are 2 coins,coin 1 and coin 2.

Is that the coin? The coin?

All of the equally likely events.

The tails side is very nice.

Like a coin? No.

Could I see the quarter?

And then, 1 of the coins is a two sided head coin.

The first coin flip might also come up tails, in which case I pick a very different coin.

The coin.

Are you a coin collector?

FIFTY COINS

There's 3 different things happening.

Let me now flip that coin once, and I want you to tell me, what's the probability that this coin which could be 50 chance fair coin and 50 chance a loaded coin.

I need, Don Corleone, those politicians you are carrying in your pocket.

There is a solution. The solution is to fake it or more precisely to add fake data.

Suppose I flip a coin, and the coin comes up tails or heads.

Liz... have you got a quid?

My 18month chip.

Change, I mean. Coins.

She took coins from the fontana?

This is going to be equal to the probability that you get 5 out of 5 heads given let's call that a normal coin given a normal coin times the probability that you had a normal coin times the probability of

So once again, we can't call them equally likely events.

Here's what I'm going to do. I'm going to grab a random coin with 50 chance.

So now what happens is, I'm going to remove one of the coins from this bag, and each coin, coin 1 or coin 2, is being picked with equal probability.

Let's go back to probability and go back to our simplest of all examples that of a coin flip.

So let's say I have a bag full of coins.

We have a bag filled with coins. Each of these coins maybe a bit different.

With the Central Limit Theorem, things become really easy.

Fair coins always come up 50 heads or tails.

Anton Vanko is the other side of that coin.

So we could say in general, that the probability of me getting 5 out of 5 coins, given that I got a normal coin times the probability that I got the normal coin that is going to be equal that 5 out of 5 happens and I got the normal.

Let's toss up for it.

Let's decide by coin toss.

Stacy... I need the coins.

What could you possibly want with those?

Well, there are 9 normal coins out of the 10 equally

This is the expression over here. Let's practice this one last time.

And this expression equals 0.6080 and so the probability that we have the same coin is simply the probability that we both have type 1 or fair coins, plus the probability of my having coin 2 times the probability of your having coin 2.

Quickly, give me the following numbers of the probability of coming up tails for coin 1 and for coin 2.

Check all that apply. Also, assume that the probability of heads is neither 0 or 1.

Dan Jurafsky Does Lufthansa serve breakfast and San Jose? Well, that sounds funny.

Let's assume there are two coins equally distributed, same probability of having each.

My hobby is collecting coins.

learn in this video.