We have a positive coefficient out here.

Let's say we had negative x squared everything we've done so far had a positive coefficient, a positive 1 coefficient on the x squared term.

I just took half of this coefficient, squared it, got positive 9 4.

Coefficient.

Real coefficient

Imaginary coefficient

leading coefficient.

And notice this coefficient is the same as that coefficient.

China s coefficient is 0.47.

Target values Gini coefficient

That's the fifth coefficient.

What's the sixth coefficient?

This coefficient becomes 4.

The coefficient is 1.

If we can't get a 1 coefficient, we'll at least have a lower coefficient here.

Times its coefficient times the fifth term's coefficient divided by 5, for the fifth term.

The leading coefficient of the first row is 1 2 is the leading coefficient of the second row 4 is the leading coefficient of the third row, and the last row does not have a leading coefficient.

The first coefficient is 1.

So, the coefficient is 1.

The coefficient here is 1.

We determined the undetermined coefficient.

The coefficient here is 11.

The coefficient there is 1.

The coefficient there is 2.

Pass the first coefficient down 3.

That becomes the new coefficient, right.

that is, what's the coefficient matrix?

By the inverse of the coefficient.

3 The Gini coefficient (coefficient of income concentration) makes it possible to numerically assess the degree of inequality.

You have to look at all of the factors here, play with the positive and negative signs, see which of those factors when one is positive, one is negative, add up to the coefficient on the x term.

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

The leading coefficient here, the coefficient on the highest degree term in standard form it's already in standard form

The simple correlation coefficient is about 0.9!

The coefficient (1.4552210935) calculation is shown below.

3 is the coefficient on the x.

linear differential equation with a constant coefficient.

Now I just used the word coefficient.

So what's 1 2 of this coefficient?

So the coefficient of friction tells us

And remember coefficient of friction are unitless

In the next few videos, we'll use coefficient of friction or calculate coefficient of friction to do some more problems

I'll do a video on why sometimes a coefficient of static friction can be different than the coefficient of kinetic friction

So we can say this generally coefficient of kinetic friction is less than or equal to the coefficient of static friction

These are the same surfaces is why should the coefficient of friction here why should the coefficient of static friction so this is here, this is stationary what's under place of coefficient of static friction why should that be larger than the coefficient of kinetic friction over here?

And the interesting thing here is that the coefficient the way I've set up this problem the coefficient of kinetic friction is lower, if we assume the same materials than the coefficient of static friction