This meant they must have been closer together in the past.

it's a theory.

I'm asking if it's possible.

Well, I do think there's a good framework for thinking.

He wins his arguments by logical reasoning.

For every one of every two of these horses, there's one dog.

We're born problem solvers.

I have a theory, but the, uh...

And numbers in between give you the gray levels of uncertainty.

Now I want to talk about approximate inference by means of sampling.

There's the audience in rhetorical arguments.

Y is either zero or one, but if you are using

Generally I think there are what I mean by that is, boil things down to their fundamental truths and reason up from there, as opposed to reasoning by analogy.

On our fourth rung, a very crucial thing happens.

This one has no y at all in it.

Here's my argument. Does it work? Is it any good?

What data and observations did you filter in as a result of your beliefs, and why?

We don't care about the test result as much as we care about the fact whether we have cancer or not.

I call it an inevitable conclusion based on reprehensible process of reasoning.

But thinking is really very straightforward it's just sort of some kind of logical reasoning, or something.

You might have guess it correctly. It's the uniform distribution.

So this unit is a tough one.

We have a very adaptive sort of online type inference algorithm.

Eventually, I was able to deduce most of their huge logical alphabet.

The next technique for efficient inference is to maximize independence of variables.

For example, a network that's a linear string of variables,

I'm unable to deduce without a firsthand examination.

So, we know what the probability of B given the different values for A, and what we care about in this specific instance is called diagnostic reasoning, which is the inverse of the causal reasoning, the probability of A given B or similarly, probability of A given not B.

And those 2 variables in turn have an effect on whether the grass gets wet.

And the key idea to Bayesian inference is you have two sources of information from which to make your inference.

They are interested in abstract reasoning.

Do you have any theories as to what caused this?

So hopefully you found that helpful, and we're going to build on this later on in some of our inferential statistics.

I inferred from our conversation that he was unhappy with his job.

And that's when you're given a couple of examples and you generalize.

Well, let's go through it.

We need to state the facts.

R of (A, B) and R of (B, C) implies R (A, C).

Coming up with proper precondition, postcondition, and invariant can be a hard task.

I will not speculate as to what might have happened.

And he says, It seems as if the ideal argument for most philosophers is you give your audience the premises and then you give them the inferences and the conclusion, and if they don't accept the conclusion, they die.

And so the fallacy that we need this resource and we can actually make it in a time frame that is meaningful is not possible.

but... all diagnosis begins with

The expectation is that they read quickly.

You might have heard about Bayes Rule before.