So just to remind you, here's some code for computing the clustering coefficient of a graph with respect to a particular node v.

Modulus

Because I like to put the z squared, I like that one to be positive.

And X1 and X2. Okay?

And that's true of any sample statistic.

Correlation

Extinction

Cooling factor

So I can just rewrite that as A so now A is not a function anymore, it's just a number A times the second derivative of y, with respect to x, plus B times the first derivative, plus C times y.

You've got gravity, you've got the centrifugal force, you've got the fluid dynamics.

AMS Binomial Expression

Scale by factor

n Choose m

Next I want to focus for a little while on the notion of a clustering coefficient.

This is supposed to be a constant

Then, we can apply that to the multiple regression example.

So there's a fair amount of interconnection between a node's neighbors.

So just getting it correct to a couple of digits is probably sufficient.

2nd derivative r squared.

Then. We would if we used any one predictor by itself.

And the reason we did that is so that we could see exactly how the regression coefficients are estimated in a multiple regression.

Now it's about eighteen.

Normal Binomial

Displaystyle Binomial

Textstyle Binomial

So we'd like to have a way of getting a pretty good answer in time a lot less than this.

Are you a cashier, not?

We'll come back to that again in multiple regression, and in lecture nine in R. And then, the importance of this distinction between unstandardi zed and standardized regression coefficients.

How strong is the relationship?

But again, now that we're in multiple regression, this is not the same as the correlation coefficient.

But let's look at on base percentage.

They're on the same side of the equation.

So let's multiply both sides by negative 3, right?

Maybe it's the porn tape. He doesn't have a porn tape.

Let's just solve x squared minus x minus thirty is equal to zero.

I think you see what I did.

(Charles) They arrested a middleman who was transporting the materials.

So, I just said and look, the a is just the coefficient on the x term, right? a is the coefficient on the x squared term. b is the coefficient on the x term, and c is the constant.

And these are the exact formulas I used in the exact case.

You literally just look at this coefficient right here, and you say, OK, well what's half of that coefficient?

When we complete the square, we just take half of this coefficient.

Low error factor

And let's see whether this is equal to 0.

So a plus b will be equal to the middle coefficient.

We have x of 1, 2, and 3 and y of 4, 7, and 13.