Correlation

Okay, so. A correlation, this simply defining correlation.

Max. vertex blend matrices

TNEF Correlation Key

That's called correlation.

You know, you load and save vectors and matrices, load and save data, put together matrices to create bigger matrices, index into or select specific elements on the matrices.

Given two matrices like these,

Specifically the correlation analysis.

Slight high correlation, or puh, puh, sorry, positive correlation for high SES.

Let's think about these 2 matrices.

How do you manipulate these matrices?

Can I multiply these two matrices?

Returns this matrices called magic squares.

Remember from the lecture on correlation, then, that represents the covariance or correlation.

So they only exist for square matrices. And then, sometimes, you can't even invert square matrices.

So the correlation is low.

It's an extraordinarily close correlation.

We could observe a correlation.

Just to give you a sense of the correlation, the correlation is about .5.

Talk about what are matrices and vectors. Talk about how to add, subtract, multiply matrices and vectors.

So let me think of two matrices.

Now let's look at vectors and matrices.

Working with matrices that don't have inverses.

Our plan now is we compute the Phi correlation for each line, and then we rank the lines from high correlation to low correlation.

But we'll look at the correlation analysis and you'll see that that's the correlation coefficient.

And that's how we added matrices so maybe it's a natural extension to multiply matrices the same way.

Because you know from the first video we did on matrices, that you can't add these two matrices.

Correlation in itself doesn't prove causality.

We're almost at the correlation matrix.

Here we expect a positive correlation.

What happens if there's no correlation?

Finally, by convention, usually when writing matrices and vectors, most people will use upper case to refer to matrices.

Modify the calibration matrices on the ColorHug device

An Assistant dialog to simplify entering of matrices

An Assistant dialog to simplify inverting of matrices

So now let's learn how to multiply matrices.

Just a couple more ways to generate matrices .

And so, what does addition of matrices mean?

Inverses only exist for certain types of matrices.

Well, what did we learn about multiplying matrices?

So you can not multiply those two matrices.

But miraculously, they'll be some interesting correlation.

So the correlation is a positive.22.

The correlation coefficient is a sample statistic.

Now we see a correlation of.72.