So in the first exercise, we will calculate the mean of data.

Computed Style

Now, I want you to add the values down here and those would look really familiar because you've done so many versions of it when completing variances from data.

And in the columns, I graphed the exact same 9 data points.

Calculation canceled

Already computed intersection point

Y bx a. Please tell me what b is. Enter your answer here.

Let me just briefly summarize what we're doing.

So, the spread over here is much larger.

Will have an easy reckoning,

Soon an easy account will be taken from him.

he shall surely receive an easy reckoning

His account shall presently be taken by an easy reckoning.

He surely will receive an easy reckoning,

He will have an easy settlement.

shall be called to an easy accounting,

He truly will receive an easy reckoning

he will receive an easy reckoning,

shall have an easy reckoning

He will be judged with an easy account

will be easy,

He shall be reckoned with by an easy reckoning,

Soon will his account be taken by an easy reckoning,

Calculated estimate variance

Let's say this is what we assume is how many cupcakes we sell.

Did you learn that by just looking at data, you can already understand a lot.

It's called the Phi coefficient. The Phi coefficient starts with a table.

So again, the values of the coefficients are estimated such that the model comes up with optimal predictions.

So keeping these formulas in mind, here's a quick quiz, which I ask you to actually calculate the mean and variance for a data sequence.

What does calculate the spread is called the variance.

Here you can see the statistical results calculated from the selected histogram part. These values are available for all channels.

And don't type in anything here.

And then once we're at this point we can just calculate this.

Those are the parentheses right there.

Don't worry about visibility. Assume the pixel shader is evaluated for all of these pixels in a triangle.

So it really depends on the market value.

a, you might remember is the mean of y minus b times the mean of x.

I can do the math as long as I have a calculator.

I'll ask you know for the two different estimators what is the maximum like estimator and what is the laplacian estimator for our estimate of the probability of the outcome 1 for this die, based on that data.

That line is broken up into 32 squares.

Calculation is miles easier if you have a calculator.

That's right. They've crunched the numbers. I see you up there.

We had to start distributing the petabytes of data to our collaborating partners in order to employ local computing and storage at hundreds of different institutes.

Calculated expected estimate

Same thing happened in offices.