Classification

So first let's revisit this normal distribution.

Let me ask the hard question now.

I expect you to see.

Dispersion of the normal distribution

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

Mean of the distribution

Your purse?

The sum of all possible classes or clusters, of which there are K we draw a class at random with a prior probability of p of the class C i and then we draw data point X from the distribution correspondent with its class over here.

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.

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.

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

The class were divided in their opinion.

The class divided into two teams.

Mean value of the normal distribution

Middle value in the normal distribution

Let me make it very clear.

Then that corresponds to a

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.

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,

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

And the answer for the µ is 70,000 of this given salary increase and the new σ stays the same.

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

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.

Mean value of the standard logarithmic distribution