Overview

This is just random variables which account for non-discrete values.

Definitions

Gaussian Random Variable

fX(x)=12πσ2e(xμ)2/2σ2

Where μ can be any real number and σ>0

It has expected value and variation

E[X]=μVar[X]=σ2

It's CDF is

FX(x)=Φ(xuσ)

The probability that X is in the interval (a,b] is

P[a<Xb]=Φ(bμσ)Φ(aμσ)

Standard Normal CDF

Φ(z)=12πzeu2/2du
Note

There is also a table that is much more commonly used.

The z value can be understood as

z=xμσ

Pasted image 20241029094716.png

Standard Normal Complementary (Inverse) CDF

Can be understood as

Q(z)=P[Z>z]=12πzeu2/2du=1Φ(z).

or

Φ(z)=1Φ(z)

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