Difference between revisions of "Variance"

From timescalewiki
Jump to: navigation, search
 
(6 intermediate revisions by the same user not shown)
Line 1: Line 1:
 
Let $\mathbb{T}$ be a [[time scale]]. Let $X$ be a random variable with [[probability density function]] $f \colon \mathbb{T} \rightarrow \mathbb{R}$. Then the variance of $X$ is defined by the formula
 
Let $\mathbb{T}$ be a [[time scale]]. Let $X$ be a random variable with [[probability density function]] $f \colon \mathbb{T} \rightarrow \mathbb{R}$. Then the variance of $X$ is defined by the formula
$$\mathbb{V}ar_{\mathbb{T}}(X) = \dfrac{d^2 C_f}{dz^2}(0).$$
+
$$\mathrm{Var}_{\mathbb{T}}(X) = \dfrac{d^2 C_f}{dz^2}(0).$$
  
 
=Properties=
 
=Properties=
 
<div class="toccolours mw-collapsible mw-collapsed" style="width:800px">
 
<div class="toccolours mw-collapsible mw-collapsed" style="width:800px">
 
<strong>Theorem:</strong> The following formula holds:
 
<strong>Theorem:</strong> The following formula holds:
$$\mathbb{V}ar_{\mathbb{T}}(X) = \mathbb{E}_{\mathbb{T}}(X^2) - (\mathbb{E}_{\mathbb{T}}(X))^2.$$
+
$$\mathrm{Var}_{\mathbb{T}}(X) = \mathrm{E}_{\mathbb{T}}(X^2) - (\mathrm{E}_{\mathbb{T}}(X))^2.$$
 
<div class="mw-collapsible-content">
 
<div class="mw-collapsible-content">
<strong>Proof:</strong> proof goes here █  
+
<strong>Proof:</strong> █  
 
</div>
 
</div>
 
</div>
 
</div>
 +
 +
=Examples=
 +
[[Variance of uniform distribution]]<br />
 +
[[Variance of exponential distribution]]<br />
 +
[[Variance of gamma distribution]]<br />
 +
 +
=References=
 +
[https://mospace.umsystem.edu/xmlui/bitstream/handle/10355/29595/Matthews_2011.pdf?sequence=1 Probability theory on time scales and applications to finance and inequalities by Thomas Matthews]

Latest revision as of 15:58, 22 September 2016

Let $\mathbb{T}$ be a time scale. Let $X$ be a random variable with probability density function $f \colon \mathbb{T} \rightarrow \mathbb{R}$. Then the variance of $X$ is defined by the formula $$\mathrm{Var}_{\mathbb{T}}(X) = \dfrac{d^2 C_f}{dz^2}(0).$$

Properties

Theorem: The following formula holds: $$\mathrm{Var}_{\mathbb{T}}(X) = \mathrm{E}_{\mathbb{T}}(X^2) - (\mathrm{E}_{\mathbb{T}}(X))^2.$$

Proof:

Examples

Variance of uniform distribution
Variance of exponential distribution
Variance of gamma distribution

References

Probability theory on time scales and applications to finance and inequalities by Thomas Matthews