We have a split wing.

Modulus

His ideas carry a lot of weight.

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.

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.

They counted on monotonously to fifty.

This is supposed to be a constant

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.

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.

With a split wing we get the lift at the upper wing, and we get the propulsion at the lower wing.

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.

Why so strange

So now the regression constant is zero.

They're on the same side of the equation.

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

Asking for the standardized. Coefficients.

What is this?

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

I think you see what I did.

And here we have the character c, which stems from the second iteration of the for loop.

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.

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.

When you, do the simple regression equations.

So the important topics to take away from this segment.

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