Tricky like a raccoon.

We want to know how much longer the new route is.

That can be tricky here at Monte Carlo.

Then comparing them with observations of real universe is an even, trickier yet.

R is make sure you understand your working directory and set your working directory.

It's a creative activity. It's fun stuff.

Only raccoons could be this tricky.

Which is like in scalers, taking two times the inverse of two a half, with getting the result one, and here's the identity matrix.

1, 1, 2, 3, 4, 4. Here I have two 1's and I have two 4's.

That was tricky.

Right?

We can ostensibly measure Hubble constant.

You can do this with any Redshift survey, and it, it was indeed done so.

In producing such a cause effect chain automatically is your homework.

An easy way to think about multiplication or timesing something is it's just a simple way of doing addition over and over again.

R is a little bit tricky.

So it's 0 times 1, minus 1 times 1.

The Bag of Words representation is the following.

2 times negative 1.

So 1 plus 1 plus 1 plus 1 plus 1 plus 1 (let's see... that's 1, 2, 3, 4, 5, 6) plus 1 plus 1 is equal to 8.

And over here, we have nine things with a mass of one kilogram, which we could write as 1 1 1 1 1 1 1 1 1.

So the first expression is 0 and the second one is going to be 0 as well.

This map is going to produce the same result as the previous one.

In the meanwhile, let me conclude the first part of my show by doing something a little trickier.

1 1

1 1

I'll label it negative 1 comma negative 1.

So it's 0 times 1, which is 0.

And if we wanted to write this down as a repeated addition, well this is literally 8 ones.

Suppose we have a distribution over those cells such as this one

Let me put commas here so it doesn't look like eleven.

What's 1 2 minus 3 2?

So what's the pattern as we take the derivatives?

So we cross out row 3, column 2.

Weinberg was also the original inventor of the pressurized water reactor.

So we're going to do (1 2) first, and then subtract 3 and then subtract 4.

So I say, 80 plus 81 plus 87 plus 88.

1, 1, minus 2.

Well I get 1! This right here is 1

Then with sigma squared it's 2.

that's most of it. Here.

Choose one of the following as the correction factor.

In particular, let's start with the variance.

In the example I've chosen here are the measurements of 5., 6., 7., 9., and 10.

The answer is 2 if we multiply the data point the first expression and the second expression get 1 1 which is 1, 0, and 1 again that adds up to 2.