These are old faculty salaries.

There's also a measurement update step where we use the measurement z.

Is that good or bad?

And they estimated that in 2008,

And then I'll observe again the 2.

Now we just repeat. We look at the next measurement. We weight particles accordingly.

Forecast

The other equation is the prediction equation, so let's go from X1 to X2.

Bush count 'em again ... You can violate your expectations about experience.

Your uncertainty shrinks to 3.99, which is slightly better than the measurement uncertainty.

Anticipation.

The arrow calculation, the matrix S with a transpose, the Kalman gain K with the inverse, back to my next prediction and my measurement update, and this is the prediction step.

This could be the cause. This could be the cause. This could be the cause.

Do research where two models are competing against one another.

And in this example, I wanna use working memory capacity to predict, SAT.

In Kalman filters we iterate measurement and motion.

Here are my best guesses. Okay?

You obviously do what the precautionary principle suggests, you try to anticipate it, but after anticipating it, you constantly asses it, not just once, but eternally.

And it goes over here?

Take upstairs.

We're expecting resistance

And at this point, we decided

What I'm going to try to do is explain to you quickly how to predict, and illustrate it with some predictions about what Iran is going to do in the next couple of years.

Formally, this operation of bringing in everything that c could become, because we're expecting to see a c, is known as predicting.

They'll say, I think this company is not going to change.

They can keep this information straight and that means that we can process the information.

Before, when we just did simple regression, that was our equation.

Proportional to the magnitude of corresponding quakes.

They're in really good shape to anticipate what we're going to want next.

XTide Tide Predictor

Monthly estimates

The wind can often be unpredictable

That's a bit unusual.

That would be descriptive statistics.

Here is the demand forecast for 1998.

But most of the world in the middle are pushing forwards very fast.

There's different things you could try to do with machine learning technique.

Casualties will be high,about 18,000.

You can read the weather, you can predict the price of heating oil.

Contrast this with a child with autism playing the same game.

Maybe its growth rate slows a little bit.

I can tell you exactly what happens.

Alright, lets turn to Iran.

Give me novelty, give me familiarity.

We can violate your expectations about shape.