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(Created page with "<div class="d-none"><math> \newcommand{\NA}{{\rm NA}} \newcommand{\mat}[1]{{\bf#1}} \newcommand{\exref}[1]{\ref{##1}} \newcommand{\secstoprocess}{\all} \newcommand{\NA}{{\rm NA}} \newcommand{\mathds}{\mathbb}</math></div> Explain why it is not possible to define a uniform distribution function (see Definition) on a countably infinite sample space. '' Hint'': Assume <math>m(\omega) = a</math> for all <math>\omega</math>, where <math>0...")
 
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<div class="d-none"><math>
Explain why it is not possible to define a uniform distribution function (see [[guide:C9e774ade5#def 1.3 |Definition]])  
\newcommand{\NA}{{\rm NA}}
\newcommand{\mat}[1]{{\bf#1}}
\newcommand{\exref}[1]{\ref{##1}}
\newcommand{\secstoprocess}{\all}
\newcommand{\NA}{{\rm NA}}
\newcommand{\mathds}{\mathbb}</math></div> Explain why it is not possible to define a
uniform distribution function (see [[guide:C9e774ade5#def 1.3 |Definition]])  
on a countably infinite sample space.  '' Hint'': Assume <math>m(\omega) = a</math>
on a countably infinite sample space.  '' Hint'': Assume <math>m(\omega) = a</math>
for all
for all <math>\omega</math>, where <math>0 \leq a \leq 1</math>.  Does <math>m(\omega)</math> have all the properties
<math>\omega</math>, where <math>0 \leq a \leq 1</math>.  Does <math>m(\omega)</math> have all the properties
of a distribution function?
of
a distribution function?

Latest revision as of 21:07, 12 June 2024

Explain why it is not possible to define a uniform distribution function (see Definition) on a countably infinite sample space. Hint: Assume [math]m(\omega) = a[/math] for all [math]\omega[/math], where [math]0 \leq a \leq 1[/math]. Does [math]m(\omega)[/math] have all the properties of a distribution function?