As a result, this function is really interesting.

And your new sigma square is your old sigma square plus a variance of the motion Gaussian.

Enhancing grav plating.

And these are exactly the same calculations as before when we fit a Gaussian but just weighted by the soft correspondence of a data point to each Gaussian.

So first let's revisit this normal distribution.

Let me ask the hard question now.

Earth Acceleration

Dispersion of the normal distribution

What we're going to do, is assume that the feature,

Mean of the distribution

Your purse?

Grav plating's at 20 Gs.

Thus, I suspect that each of these examples was distributed according to a normal distribution or

And so therefore, their kinetic energy can be characterized by a velocity dispersion.

This tells you the height of the normal distribution function.

0 density, 1 distribution

And, there's a standard deviation of the distribution of sample means, standard air.

little higher than if you do it, uh, orally. So we looked at this histogram before.

In this video, I'd like to talk about the Gaussian distribution, which is also called the normal distribution.

Our class robot has built in noise variables. One is for forward motion.

Finally the shape of this distribution of sample means will be approximately normal even if the distribution in the population isn't normal.

A heavy purse makes a light heart.

Linear middle of the distribution

Standard deviation of the distribution

Degrees of freedom for the t distribution

You learned something really important.

Putting it in population parameters, but putting it in sample statistics.

Mean value of the normal distribution

Middle value in the normal distribution

Let me make it very clear.

Then that corresponds to a

I have another Gaussian question for you this is called a heavytail Gaussian.

And I have to explain to you, the top of this graph shows you that frequency distribution that I talked about.

Then we have a Gaussian distribution that is centered around zero, because that's Mu.

If you remember from lecture two when we started to talk about probability, we can use the normal distribution.

Let's put this into action.

You did it. Fold the blanket and the sheet back together.

So I can get any value less than 20 given this distribution.

MV is the linear middle of the distribution.

STD is the standard deviation of the distribution.

Standard deviation of the normal distribution

Let's just go back to our example and see what an amazing thing you've just programmed.

When I've done this as many time as I have measurements and motions,

It's one standard deviation in the distribution of sample means. So this distribution of sample means, again.

Look at the new locations. Texas,