It's extremely unlikely given the assumption that everybody's healthy.

An assumption and only an assumption.

And this is a huge assumption.

That's why this assumption is important.

The assumption is something like this.

Given, that's that vertical bar, you can read that as given The assumption that the null hypothesis is true.

And finally there's this assumption of homoskedasticity.

Given, this means given

And this risk free is the big assumption.

And given that we do and that's the assumption everybody, I think, in this room would make when was that?

More data? Making the Markov assumption rather than naive Bayes assumption?

The conditional independence assumption of each pixel, given the class, is too strong an assumption in this case, but it's fun to talk about image recognition in the context of Naive Bayes regardless.

That's just an assumption.

It's all assumption driven.

Seems the logical assumption.

What the P value really means is it's the probability of obtaining this outcome given the assumption that the null is true.

This is under the assumption that there's no parallel arcs.

Let's test this assumption by heading over to Eastern Europe.

And then this upper line, this means given given that

The probability of landing way out there given the assumption that the null is true is really low.

What about the second assumption?

Because we'll see later in this video that to some degree, that assumption is one of the biggest drivers of assumption.

Now this is a totally reasonable assumption, given that I have made quite a habit of encouraging people to spend more time playing games.

So this is the assumption that you get in on that.

This is a feasible goal, basically because, contrary to widespread assumption,

This brings me to the third, and perhaps most problematic, assumption

So given this angle.

That's a big assumption, and we could test whether or not that assumption is valid.

Would it be helpful to make a Markov assumption rather than the naive Bayes assumption?

So given this formula and given our input string

It's a reasonable assumption I think.

That's one hell of an assumption.

But that assumption was a problem.

Perhaps it was just an assumption.

Using this assumption, he was able to explain some properties of light.

Given this data set, an

This formula is given here.

Stationarity assumption we can write as the probability of a word given the previous word is the same for all variables.

In this case, the problem really comes down to the naive Bayes assumption is a weak one, and the Markov assumption would do much better.

She put on an assumption of ignorance.

What he said bears out my assumption.

Given this URL, it would load this image.

We've given this person a name.

This is usually given to epileptics.

That's one of the reasons why making this naive Bayes assumption is so helpful.