And how they can tell us a lot about what's going on in our data.

But just to be clear.

Correlation

I am just gonna pause for a moment to let you think about that.

But there is zero correlation between IQ and emotional empathy, feeling with the other person.

What about causality?

Unfortunately, it's not, because I would like to be taller, but I'm not.

Though there's plenty who would.

In MCMC, that's not true.

Throughout this whole thing, making toys,

Correlations can range from positive one, which is a perfect positive correlation.

And, I'll show you the correlation matrix in a moment.

The answer is yes clearly for different values of A, I get different values of B.

It's smaller than 0 if the relationship is negative.

But there's a fair bit of variation around it, so I would say that the relationship is linear but not exact.

So the important topics to take away from this segment.

The data came back from the United States, from England, from Sweden, from Canada, and it was all the same no correlation, no connection, none at all.

There's no communication.

This is bullshit, come on.

What about the second assumption?

And that's true of any sample statistic.

If that's how bad you don't want to do it, then break the contract and leave then!

No, it has absolutely nothing to do with the deposition.

Good relationships, bad relationships, annoying relationships, agnostic relationships, and what I'm going to do is focus on the central piece of an interaction that goes on in a relationship.

Obviously that depends on the magnitude of the co relation.

And now the data sits, a square in which data is uniformly arranged, correlated, yes or no?

He held up a Liquor store and got shot. If he dies, it's your fault.

Just recall what a positive and negative relationship are a couple of simplified examples.

It's larger than 0. If there's a positive relationship between x and y.

And we want to come up with a correlation between coverage on one side, and outcome of the run on the other side.

So that's an important point too.

And there are different kinds of relationships between the people.

If someone, for example, shows you the salary of a person and the age of a person, you can say they're really correlated, or you could say they're not correlated at all.

And they can do it because they don't link causation and correlation.

Not just it coincides with the fact that you die and very frequently people in the public get this wrong.

But the question I wanna pose to you. And I, I don't have a slide after this one.

In the middle of this distribution. What that means is if I did the study over, and over, and over again.

So, final slide, the important topics to take away is...

That has nothing to do with you.

I suppose I am affiliated...

The universality, to repeat, is us that we are the city.

The important topics to take away from segment one is just again, what is a correlation?

I work 10 hours a day I commute two hours a day.

Yes, there is.

It's 1. Again, 2 18 gives us 36. Square root is 6.