# Taylor Series

# Bra-kets Notation

# Probabilities

## Bayes’ theorem

## Mean/Expectation value

For

xbeing an event mapped by random variableX

For any function

fthat takesxas an input

For discrete case

## Corelations

## Covariance

Variance, squire of S.D.

Covariance Matrix

## Moments

The n-th moments of

f(x)about pointc

The n-th moment of random variable X, simply replace

f(x)withp(x)

The n-th central moment of random variable X, the 2-nd central moment is variance

# Domain Transforms

## Fourier Transform

Continuous

Discrete

## Laplace Transform (Z-Transform)

First Define

Continuous

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