We're going to use that normal distribution a lot.

And for this analysis, let's assume that we had 40 athletes that were tested twice.

That's exactly what we're going to do in inferential statistics.

Here are the 1,100 bottle caps they collected.

Definitely didn't picture my demise like this.

You didn't expect that, did you?

And that's our answer. f of z is negative 2z plus 3.

Expect the unexpected.

We're finding it 11 times more powerful than email.

You could say look, I performed services that will earn me 200 in the future

We would lose that if we just looked at

Let's call that, you know, this is y is equal to some function of x.

The cubicle in the center aisle with the view of the ladies room instead?

What's the estimate?

Judge Toomey granted the opposition a onemonth continuance, which we expected under the circumstances.

Wow. Crap. I, uh

You know you could view this as the first coordinate.

He assumed that the man was hiding something from him.

That is his main fault, but on the whole he's a good worker.

So all memory is sophisticated and dynamic, but if just for simplicity, let's imagine memory as a movie clip.

The witness lied.It's not her fault.

They took inspiration from, of all things,

But it shows the intelligence that the elephants have.

And again I'll be using the impact data as our example.

Here's the routine. It's very short.

You never saw this.

That's new.

And I just simulated data in R. That's real easy to do, I'll show you how to do that in ah, in the Intro To R lecture.

When I first ate a tomato grown on this, I couldn't believe how sweet it was.

It wasn't exactly what I had in mind.

Now we have two predictors, its X1 X2. Remember this is a linear model and its additive.

And sure enough, we cancel those out.

If you have more questions about it, ask Kevin Kelly later. (Laughter)

We compiled all the information about where the Native Americans were, the Lenape.

How come you didn't figure the outside lamps?

Now, as we go to the local picture, we do a lot of local roll outs,

Before we're done with localization, I'd like to talk about robot motion.

And if the light is green, then the traffic should go.

I don't know... Treos or Blackberry.

And, different models will have different curves in that diagram.

I counted on everyone's confusion in the dark.

That's exactly what we're gonna do in inferential statistics.

OK. That completely destroys the relationship between the business and the sidewalk, where the theoretical pedestrians are.

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There's a Frenchman who can help, another thinker who didn't define comedy because he expressly didn't want to.