And liquidity.

And let's say for whatever reason, all of these other

That's insolvency.

It's about as mysterious as the liquidity of water.

Liquid means it's very easy to buy and sell those securities in large quantities.

Beyond drag, lift and stretch there are many other properties we could simulate.

And frankly, you might be uncertain about

And that is opposed illiquidity.

Illiquidity is a different situation.

In the next video, I'll talk a bit about the Gaussian distribution and review properties of the Gaussian probability distribution, and in videos after that, we will apply it to develop an anomaly detection algorithm.

We then move to the right a total of 10, with a motion uncertainty of 6.

You couldn't do it.

I'm worth 11,000.

So the mode is a useful statistic if your distribution of data is what is called multimodal.

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.

And I can sell them.

So first let's revisit this normal distribution.

Dispersion of the normal distribution

Mean of the distribution

Your purse?

Check the corresponding box if the attribute applies.

Is floating

So now I have two problems. I have this and I have this.

So once again, I'm stuck holding this non liquid asset.

I'm going to ask you now for the initial distribution that I'm writing up here, can you give me the distribution after the motion?

For example, government treasuries is a liquid security or a liquid asset,

Consider this.

This tells you the height of the normal distribution function.

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

Plus it's not a man purse.

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

What does it mean to look at it from multiple perspectives?

And you might not even be able to find anyone to buy it a year later.

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.

But there will be at least some type of a market in the security, so you could have what you could call liquidity.

So there's a couple of issues here.

Safety because you know that this earnings stream is guaranteed.

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