We distributed these rapid transport corridors throughout the city center, and extended them into the outskirts.

So first let's revisit this normal distribution.

Let me ask the hard question now.

Dispersion of the normal distribution

We have 14, was the peak in that histogram.

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

Mean of the distribution

Your purse?

When you actually use the Excel normal distribution function,

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 similarly I'm going to assume that X2 is distributed, Gaussian, that's what this little tilda stands for, that means distributed Gaussian with mean mu2 and Sigma squared 2, so it's distributed according to a different Gaussian, which has a different set of parameters, mu2 sigma square 2.

Here is an example of a particular cluster, where different contours show, say, average distribution of galaxy light, or the number density, or the inferred galaxy mass, or mass distribution for the whole cluster.

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.

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

Linear middle of the distribution

Standard deviation of the distribution

Degrees of freedom for the t distribution

You learned something really important.

Yeah. Just get high enough.

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

We have a weighted mean over here.

There's 500 in there and the wallet's worth more than that.

Mean value of the normal distribution

Middle value in the normal distribution

Let me make it very clear.

Then that corresponds to a

Where we assume that 30 wine experts rated the overall quality of four different wines on a scale of one to ten, and ten is highest quality.

luminous matter changes is a function of mass.

And that's because this value tells the probability that you're less.

Let me give you a final example in which I assume a uniform distribution, and I want you to fill in for me the distribution after motion.

less fluctuation in those sample means. So then, if I plotted all my sample means.

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.

The woman's handbag.

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

A 2 dimensional gaussian is defined over that space, and it's possible to draw the contour lines of the gaussian.

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

Starting with the following source code,

And we also know that most of them live or lived in Asia.

MV is the linear middle of the distribution.