Turn of that valve.

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.

Modulus

If they were then you might have a confound in your study. So lets go back and look at the scatter plot, relating working memory capacity SAT.

JH That's fantastic.

The secondary flow valve should be behind you and to your right.

Turbine release valve, activated.

This is supposed to be a constant

We've taken this information and we've made a mathematical model out of it.

2nd derivative r squared.

And that's true of any sample statistic.

Open Valves 3 and 5.

I have it right here.

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.

But before we began, our land looked like that.

They're combatting that effect of age. If we now take into account active years.

Females after their first calf is already weaned a lower load.

They are statistics that describe.

Correlation

Extinction

Cooling factor

By 15 years later, by 1850, doing the same thing

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

Water valve's sprung a leak.

Now look for the emergency valve release sequence.

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.

Now it's about eighteen.

So here we go.

Now let's think about what happens with the number of suppliers.

The Gulf of Mexico is a very big ocean.

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.

I think you see what I did.

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

They're on the same side of the equation.

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.

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

So the important topics to take away from this segment.

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