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

I've changed the random variable now.

Is the idea of a random Variable

let's look at some actual random variable definitions.

So this is clearly a discrete random variable.

So this one is clearly a continuous 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.

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

So is this a discrete or a continuous random variable?

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.

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

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

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.

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.

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

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

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.

A random variable can take on many, many, many, many, many many different values with different probabilities.

This is fun, so let's keep doing more of these. Let's say that I have random variable X.

Let's think about let's say that random variable Y, instead of it being this, let's say it's the year that a random student in the class was born.

Random

Random

Random

random

Random

It's not random. Random is easy.

There's no way for you to count the number of values that a continuous random variable can take on.

Variable like this endurance variable.

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

Now I'm going to define random variable X to be the winning time now let me write it this way.