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Reexamination of the data is required to make the formula accurate.

How real is the threat?

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Okay so we're going to enter in real data.

You know, these are things that we have good physiological reasons to expect to see stressed caused by this transience.

I don't know.

It turns out that it's impossible to capture balanced parentheses with a regular expression.

The data is often inaccurate.

This data is incorrect.

There's M data points.

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And the challenge is really found in this picture here.

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I can't be sure.

Nothing concrete.

And if they're different, that indicates a bug.

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Target sighted.

Target acquired.

And there's another cognitive bias

I need some real proof.

First, I want you to remove the outliers by only extracting data between the lower and upper quartile.

You can crossreference with the files.

Ethan Shaw confirmed.

Let me quickly go over the proof.

But instead of trying to figure out whether the data supplies sufficient evidence to conclude that the engines meet the actual emissions requirement, and all of the hypothesis testing, I thought I would also use the same data that we had in the last video to actually come up with a 95 confidence interval.

The evidence is conclusive.

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So how does it work?

I want to be sure about this. Ask the station chief from Rabat to confirm the deaths and do a subrosa collection of the bodies.

What this means is you can gather more and more data around a hypothesis or a positioning, and it will strengthen it, but it will not conclusively prove it.

And you can't do a reverse inference here. You can't say that.

Why?

Thirtyseven percent and probable don't belong in the same sentence.

Grid on contact.

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I proved the fact on the strength of the data.

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