00:02
In order to find the rank correlation coefficient, we're going to use spearman's formula, which is pictured here on the right.
00:09
So row is the spearman's rank correlation coefficient.
00:14
D .i.
00:15
Is going to be each of the differences between the first and second terms of our sets a and b respectively.
00:24
And then n is going to be the number of observations in this case 15.
00:27
We've got 15 observations here.
00:30
So to start finding what the values are for each of these, let's compute the sum of all the d .i.
00:35
Squares first, and then we'll plug it in from there.
00:38
So again, di is going to be the difference between the a ranking and the b ranking for each of these terms.
00:44
So let's go ahead.
00:46
And so we're going to have d0 squared, d1 squared, and so forth through d15 squares, where we're computing now.
00:56
So the difference between 1 and 10 is 9.
00:59
9 squared is 81.
01:01
Do that again, two and seven.
01:03
The difference is five.
01:04
Five squared is 25 and so forth.
01:07
So we're just going down here, finding the differences in squaring them each time.
01:12
And so that's all i'm doing here.
01:13
And after we finish squaring each of these, you can see we're almost to the end already.
01:17
I'm going to go ahead and sum up all these numbers because when we see it's capital sigma here, that's a summation.
01:25
And we're going to want to find the sum of all of these d .i.
01:30
Squares.
01:34
So just clumping these up in some little groupings to make our addition easier.
01:39
One, two, three, four, five, six fours together.
01:44
That's going to give us six fours is 24...