# AP Statistics Curriculum 2007 Cauchy

(Difference between revisions)
 Revision as of 21:58, 30 June 2011 (view source)JayZzz (Talk | contribs) (Created page with '== General Advance-Placement (AP) Statistics Curriculum - Cauchy Distribution== === Cauchy Distribution === The standard Cauchy distribution i…')← Older edit Current revision as of 22:38, 18 July 2011 (view source)JayZzz (Talk | contribs) (→Cauchy Distribution) (4 intermediate revisions not shown) Line 2: Line 2: === Cauchy Distribution === === Cauchy Distribution === - The standard Cauchy distribution is derived from the ratio of two independent Normal distributions. If X ~ N(0,1), and Y ~ N(0,1), then $\tfrac{X}{Y} \sim Cauchy(0,1)$ + The standard Cauchy distribution is derived from the ratio of two independent [http://wiki.stat.ucla.edu/socr/index.php/AP_Statistics_Curriculum_2007_Normal_Std Normal Distributions]. If X ~ N(0,1), and Y ~ N(0,1), then $\tfrac{X}{Y} \sim Cauchy(0,1)$ The Cauchy distribution is important in physics (where it’s known as the Lorentz distribution) because it’s the solution to the differential equation describing forced resonance. In spectroscopy, it is the description of the shape of spectral lines which are subject to homogeneous broadening in which all atoms interact in the same way with the frequency range contained in the line shape. The Cauchy distribution is important in physics (where it’s known as the Lorentz distribution) because it’s the solution to the differential equation describing forced resonance. In spectroscopy, it is the description of the shape of spectral lines which are subject to homogeneous broadening in which all atoms interact in the same way with the frequency range contained in the line shape. Line 16: Line 16: '''Median''':
'''Median''':
+ $x_0\!$ + + '''Mode''':
$x_0\!$ $x_0\!$ Line 24: Line 27: $x \in (-\infty, +\infty)\!$ $x \in (-\infty, +\infty)\!$ - '''1st Moment''':
+ '''Moment Generating Function'''
- None + Does Not Exist - + - '''2nd Moment''':
+ - None + - + - '''Kth Moment''':
+ - None + ===Applications=== ===Applications=== Line 55: Line 52: * SOCR Home page: http://www.socr.ucla.edu * SOCR Home page: http://www.socr.ucla.edu - {{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_Data_LA_Neighborhoods_Data}} + {{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php/AP_Statistics_Curriculum_2007_Cauchy}}

## General Advance-Placement (AP) Statistics Curriculum - Cauchy Distribution

### Cauchy Distribution

The standard Cauchy distribution is derived from the ratio of two independent Normal Distributions. If X ~ N(0,1), and Y ~ N(0,1), then $\tfrac{X}{Y} \sim Cauchy(0,1)$

The Cauchy distribution is important in physics (where it’s known as the Lorentz distribution) because it’s the solution to the differential equation describing forced resonance. In spectroscopy, it is the description of the shape of spectral lines which are subject to homogeneous broadening in which all atoms interact in the same way with the frequency range contained in the line shape.

PDF:
$\frac{1}{\pi\gamma\,\left[1 + \left(\frac{x-x_0}{\gamma}\right)^2\right]}\!$

CDF:
$\frac{1}{\pi} \arctan\left(\frac{x-x_0}{\gamma}\right)+\frac{1}{2}\!$

Mean:
Does Not Exist

Median:
$x_0\!$

Mode:
$x_0\!$

Variance:
Does Not Exist

Support:
$x \in (-\infty, +\infty)\!$

Moment Generating Function
Does Not Exist

### Applications

$\cdot$ Used in mechanical and electrical theory, physical anthropology and measurement and calibration problems.

$\cdot$ In physics it is called a Lorentzian distribution, where it is the distribution of the energy of an unstable state in quantum mechanics.

$\cdot$ Also used to model the points of impact of a fixed straight line of particles emitted from a point source.

### Example

http://www.distributome.org/ -> SOCR -> Distributions -> Distributome

http://www.distributome.org/ -> SOCR -> Distributions -> Cauchy Distribution

http://www.distributome.org/ -> SOCR -> Functors -> Cauchy Distribution

SOCR Cauchy Distribution calculator (http://socr.ucla.edu/htmls/dist/Cauchy_Distribution.html)