Scatter Chart

Stock Chart

Gantt Chart

Dispersion of the normal distribution

You spend a certain amount per bed net.

Like masssir, like I'm a slave?

You set off your bombs and turned everything to ashes.

Let me ask the hard question now.

So here's my first quiz for you on regression.

I can tell you my hand isn't really able to draw 60,000 points.

The best way to illustrate this, of course, is just scatter plots, right?

Traveling through hyperspace ain't like dustin' crops, boy!

What I want to do in this video is to generalize it.

You wanna keep them sorta short, 'cause you have to write them repeatedly in the code.

That's largely influenced by the sample size.

People always ask me, you know,

The blue and the dim and the dark cloths

Ashes to ashes...

Ashes to ashes.

They are spraying the fruit trees.

Now what is going to be the variance?

I guess the thing I haven't said about this is, it is absurdly cheap.

What is the youngest person to earn 267,000 in our data set?

Here is a very elaborate data set of people of certain ages and their wages that they receive.

I think these dinosaurs migrated we call it dispersal around the globe, with the slightest land bridge.

ADAMS Ashes to ashes, dust to dust.

Ashes to ashes,dust to dust.

Congratulations! You've finished something really complex.

And, I'd like to demonstrate a new graph, scatter plots.

Look at the residuals But, what is homoskedasticity?

Up to this point, I've just been showing you linear relationships, this regression

Whether this idea is right or some other idea is right,

We'll also look at physical endurance as it relates to activeers.

Volcanic Ash

But the average is about 50 years old in this sample.

Now looking at this same data, I'd like to ask you a different question.

In a final exercise,

My question for you is when you graph this is the data linear.

I meant the motorcycle bar, but yes.

That's the same as σ 2 over 2, which means a new variance squared is half of the old one.

They both display a negatively sloping somewhat linear relationship.

What are they used for?

What does that mean. I'll try to describe it in words, but it's best.

To Gray

Oh, just a little.