00:01
Given a random variable x, y, we say the random vector x, y is a uniform distribution.
00:13
On some, let's call it rectangle, call it r.
00:19
R is determined by 0 to the cartesian product between 0, 2, and 1.
00:34
So let's draw a graph.
00:36
Here's x, here's y, 0 here, this is 0, 2, 1.
00:45
That means our x, y is a random vector uniformly distributed in this rectangle.
00:57
By the definition of the uniform distribution, we know the joint density of x, y will be equal to 1 over the area a of r.
01:11
When i say x is greater or equal to 0, that's equal to 2, and y is greater or equal to 1, that's equal to 4, it is equal to 0.
01:23
I mean, the density is supported on this range.
01:29
That is, it is a rectangle.
01:31
It's easy for us to say ar is equal to times 0 minus 2, which is 6.
01:39
So we can just replace ar by 6.
01:47
Then this is the joint density function for fx.
01:57
Now, by this joint density function, we want to find the marginal density of x and y.
02:04
Let's begin with the marginal density for x...