Symbols:E

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exa-

$\mathrm E$

The Système Internationale d'Unités metric scaling prefix denoting $10^{\, 18 }$.


Its $\LaTeX$ code is \mathrm {E} .

Sources


Hexadecimal

$\mathrm E$ or $\mathrm e$

The hexadecimal digit $14$.


Its $\LaTeX$ code is \mathrm E  or \mathrm e.


Sources


Set

$E$

Used by some authors to denote a general set.


The $\LaTeX$ code for \(E\) is E .


Identity Element

$e$

Used to indicate the identity element in a general algebraic structure.

If $e$ is the identity of the structure $\left({S, \circ}\right)$, then a subscript is often used: $e_S$.

This is particularly common when more than one structure is under discussion.


The $\LaTeX$ code for \(e_S\) is e_S .


Sources


Euler's number

$e$

Euler's number $e$ is the base of the natural logarithm $\ln$.

It is defined to be the unique real number such that the value of the exponential function $e^x$ has the same value as the slope of the tangent line to the graph of the function.


The $\LaTeX$ code for \(e\) is e .


Sources


Experiment

$\mathcal E$


An experiment, which can conveniently be denoted $\mathcal E$, is a measure space $\left({\Omega, \Sigma, \Pr}\right)$ such that $\Pr \left({\Omega}\right) = 1$.


The $\LaTeX$ code for \(\mathcal E\) is \mathcal E .


Expectation

$E \left({X}\right)$


Let $X$ be a discrete random variable.

The expectation of $X$ is written $E \left({X}\right)$, and is defined as:

$\displaystyle E \left({X}\right) := \sum_{x \mathop \in \operatorname{Im} \left({X}\right)} x \Pr \left({X = x}\right)$

whenever the sum is absolutely convergent, that is, when:

$\displaystyle \sum_{x \mathop \in \operatorname{Im} \left({X}\right)} \left|{x \Pr \left({X = x}\right)}\right| < \infty$


The $\LaTeX$ code for \(E \left({X}\right)\) is E \left({X}\right) .


Conditional Expectation

$E \left({X \mid B}\right)$


Let $\left({\Omega, \Sigma, \Pr}\right)$ be a probability space.

Let $X$ be a discrete random variable on $\left({\Omega, \Sigma, \Pr}\right)$.

Let $B$ be an event in $\left({\Omega, \Sigma, \Pr}\right)$ such that $\Pr \left({B}\right) > 0$.


The conditional expectation of $X$ given $B$ is written $E \left({X \mid B}\right)$ and defined as:

$\displaystyle E \left({X \mid B}\right) = \sum_{x \mathop \in \operatorname{Im} \left({X}\right)} x \Pr \left({X = x \mid B}\right)$

whenever this sum converges absolutely.

Note that $\Pr \left({X = x \mid B}\right)$ denotes the conditional probability that $X = x$ given $B$.


The $\LaTeX$ code for \(E \left({X \mid B}\right)\) is E \left({X \mid B}\right) .