This might be taxing my computer by taking the screen capture with it.

And so to actually calculate this, what I do is I take the cumulative distribution function of this point and I subtract from that the cumulative distribution function of that point.

So I can get any value less than 20 given this distribution.

Now this transformation has doubled the area of the original figure, and therefore we have just learned that the area of the triangle equals the area of this rectangle divided by two.

Surface

Area

The chances that we observed in µ that's smaller than a is the same as the surface area and then the Gaussian over here.

In statistics, pi is used in the equation to calculate the area under a normal distribution curve, which comes in handy for figuring out distributions of standardized test scores, financial models, or margins of error in scientific results.

So this is a cumulative distribution function for the same... for this

And that's because this value tells the probability that you're less.

So what I would do I would figure out the area of this bathroom floor, and then divide by the area of the tiles.

That's actually what I do in the other video, just to approximate the area under the curve and give you a good sense that the normal distribution is what the binomial distribution becomes essentially, if you have many trials.

But because this is a probability distribution, the area under the curve, that is the shaded area there, that area must integrate to 1.

Anyway, the American cities

Sector Surface

So what is our area squared going to be?

It's just the product rule.

Cumulative 0 calculates the density function cumulative 1 calculates the distribution.

The area of Canada is greater than that of the United States.

So what the cumulative distribution function is essentially let me call it the cumulative distribution function it's a function of x.

a function has been defined called the cumuluative distribution function that is a useful tool for figuring out this area.

This looks interesting.

Now one profile, problem with Hubble's profile are originally envisioned, is that it diverges.

Area and Perimeter

So if we just multiply this out, let me write it here.

let's do, surface

We match the dimensions of force, drag force on one side with what we have on the other, which is area, density, speed and viscosity.

You remember this because that's what you programmed.

If I took the integral from minus infinity to infinity of d sub tau of t dt, what is this going to be equal to?

Area squared is equal to ad minus bc squared.

The determinant of this is ad minus bc, by definition.

Problem 38.

The area in central Japan.

So if you wanted to graph this right here, you would say false in caps.

So what I did is I evaluated the cumulative distribution function at one to be right there.

Let me write it this way

And then this is the height, this is the height, right over here.

Now what could I do?

Integral

Because this is longer.

Fair enough.

And they tell us that the area is 168.

Well, pressure is force divided by area.

Three square furgles . So it's the same exact area. Three square furgles is equal to twelve square feet.

So first let's revisit this normal distribution.