An assumption and only an assumption.

A loss was a loss.

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

That's just an assumption.

It's all assumption driven.

What about the second assumption?

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?

And this is a huge assumption.

It's a reasonable assumption I think.

That's why this assumption is important.

Carrier Loss Rate

Possible Data Loss

Data Loss Warning

Loss of memory.

Loss of health is more serious than loss of money.

Sputnik wasn't a technical loss, but it was a prestige loss.

She put on an assumption of ignorance.

What he said bears out my assumption.

And finally there's this assumption of homoskedasticity.

Man is certainly loss,

Loss of Color Information

Loss of Translucency Information

I take a loss.

That's your loss, lieutenant.

The loss of Moscow.

The basic law, let's say here's an assumption.

I'm not at all comfortable with that assumption.

They're making some assumption about the discount rates.

And this risk free is the big assumption.

The discount rate assumption is everything in finance.

I think six martinis is a reasonable assumption.

We'll do other videos where we talk about when it is a good assumption, when it isn't a good assumption.

And they have thereof no knowledge. They follow not except assumption, and indeed, assumption avails not against the truth at all.

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

We can make the Markov assumption and that's the assumption that the effect of one variable on another will be local.

Verily man is in loss,

Verily! Man is in loss,

Indeed we have suffered loss!

Man is indeed in loss,

Indeed, mankind is in loss,

They compensated for the loss.

I'm at a complete loss!

The loss amounted to 2,000,000.

Verily Man is in loss,