That's my random variable Z. Is this a discrete random variable or a continuous random variable?

So this is clearly a discrete random variable.

Is this a discrete or a continuous random variable?

Is this a discrete or a continuous random variable?

Is this a discrete or a continuous random variable?

We are now dealing with a discrete random variable.

So is this a discrete or a continuous random variable?

So once again, this right over here is a discrete random variable.

Is this going to be a discrete or a continuous random variable?

With a discrete random variable, you can count the values. You can list the values.

You have discrete random variables, and you have continuous random variables.

I've changed the random variable now.

Most of the times that you're dealing with, as in the case right here, a discrete random variable let me make it clear this one over here is also a discreet random variable.

But if you can list the values that it could take on, then you're dealing with a discrete random variable.

Is the idea of a random Variable

And discrete random variables, these are essentially random variables that can take on distinct or separate values.

let's look at some actual random variable definitions.

Most of the time that you're dealing with a discrete random variable, you're probably going to be dealing with a finite number of values.

So this one is clearly a continuous random variable.

Discrete

Discrete

Is this a discreet random variable or a continuous random variable? Well, the exact mass and I should probably put that qualifier here.

So this right over here is a continuous random variable.

We have random variable X and the probability of 0.2.

So let's say that I have a random variable capital X.

We can define another random variable capital Y as equal to

That's not going to be the case with a random variable.

Let's define random variable Y as equal to the mass of a random animal selected at the New

There was minus 6 plus zero ten times this Gaussian random variable.

Well, this random variable right over here can take on distinctive values.

There are discreet values that this random variable can actually take on.

And I want to think together about whether you would classify them as discrete or continuous random variables.

The probability of any random variable Y can be written as probability of Y given that some other random variable X assumes value i times probability of X equals i, sums over all possible outcomes i for the (inaudible) variable X.

Those values are discrete.

Let's say x is a real value random variable, so x is a real number.

Al, for one, looks at much more discrete decision spaces with discrete variables.

Everything else was very discrete.

They are not discrete values.

Are you crazy? Be discrete.

It's more discrete and private.

An experiment is when we have random assignment conditions and something is minipulated in independent variable.

Let's let random variable Z, capital Z, be the number ants born tomorrow in the universe.

Well now, we can actually count the actual values that this random variable can take on.

For those of you that know what a Gaussian random variable is or for those of you that know what a normal random variable is, you can also set W equals Rand N, one by three.

So just to review the expected value of some random variable x is the sum of all values that the variable can take on, the value of that variable times the probability.