That happens 37 of the time.

D gun's down to 20.

And dengue fever has grown in speed quite phenomenally.

Not enough examples.

So let's normalize it and we normalize it by the sum of the joint for cancer and the joint for non cancer.

One fifth the rate of colon and breast cancer, big killers here in America.

And the answer is 0.45.

P of not A given the same events, X1, X2, and not X3, which resolves to P of not X3 given not A,

What is the code?

And using the prior, we know that P of not C is 0.99.

Suppose we have a positive test, what do you think?

We've learned at Stanford and other places that we can discover cancer stem cells, the ones that seem to be really responsible for disease relapse.

When you receive, say, a positive test result, what you do is, you take your prior P(C) you multiply in the probability of this test result, given C, and you multiply in the probability of the test result given (Neg_BAR_ C).

He's one of our students here.

The frequency of crime in the town is high.

Here you get 0.72, which is the product of not having cancer in the first place 0.9 and the probability of getting a negative test result under the condition of not having cancer.

It seems that cancer is a direct result to injury.

And while I was reading all these articles about cancer, it seemed that the articles a lot of them focused on, you know, the genetics of breast cancer, and the genesis and the progression of breast cancer tracking the cancer through the body, tracing where it is, where it goes.

But cancers don't start out like this, and in fact, cancers don't start out with a blood supply.

We begin with our prior probability, our sensitivity and our specifitivity, and I want you to begin by filling in all the missing values.

JC Right.

But if you really understand why does a cell go from normal cell to cancer?

So this little thing over here is my shortcut of not having cancer.

The World Has Changed

Now, what's remarkable about this outcome is really what it means.

How well do these work in practice?

The joint probability of cancer and positive is 0.1 0.9. That's the joint that's not normalized.

To make this correct, we also have to compute the posterior for the non cancer option, which there is no cancer given a positive test.

He had a shot at the goose.

living downstream who are reporting alarmingly high cancer rates.

Ganba!

But once it starts moving throughout the body, that's when it becomes deadly.

And what's the same for P( C, Neg).

We just applied Bayes Rule to compute a really involved probability of having cancer after seeing a test result.

South Africa has the highest rate of unemployment in the world.

Suppose there exists a certain type of cancer, but the cancer is rare only 1 in a 1000 people has the cancer where as 999 in 1000 people don't have it, illustrated by the probability of cancer and the probability of not cancer.

Without angiogenesis, the tumor remains the size of a pinpoint and it's not harmful.

And once again, we'd like to refer the corresponding numbers over here on the right side 0.1 for the cancer times the probability of getting a negative result conditioned on having cancer and that is 0.1 0.1, which is 0.01.

Now comes the hard part

Internationally comparable data on life expectancy, on kids' maths and literacy scores, on infant mortality rates, homicide rates, proportion of the population in prison, teenage birthrates,

700 rads per shot. (Laughter)

And just as the Tasmanian devil cancer is contagious through the spread of living cancer cells, so is this dog cancer.

Chance of departure today, 100 percent.

For cancer?

Cancer can be cured if discovered in time.