Are they interconnected?

1,000 years ago this is what the world looked like.

So first let's revisit this normal distribution.

Dispersion of the normal distribution

Mean of the distribution

Your purse?

This tells you the height of the normal distribution function.

Here's my code. We have a loop for 1,000 steps.

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

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

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

Let me ask the hard question now.

Linear middle of the distribution

Standard deviation of the distribution

Degrees of freedom for the t distribution

You learned something really important.

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

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

This is my sense routine. It goes from here to down here.

I'm giving you a skeleton program, which has a function update, that takes as an input a mean and a variance for the first distribution and a mean and a variance for the second distribution and outputs the new mean and the new variance of the product of those.

Down here, I can normalize aux to have a total probability of 1, and then I return it.

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

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

Mean value of the normal distribution

Middle value in the normal distribution

So suppose we know we are looking at faces.

So we're going to put a for loop here, from t in range(T) and then after in, add all the stuff below.

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

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

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

Who are the winners and who are the losers in Iran?

0 density, 1 distribution

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

That's largely influenced by the sample size.

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

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

Intuitively speaking, this is the case because we actually gain information.

She'll need to go through and check the frequency distribution of different intervals.

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

That's called a probability histogram.

Mode 1 returns the one tailed test, Mode 2 returns the two tailed test.

Mean value of the standard logarithmic distribution