exercise:16183d0390: Difference between revisions
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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> Let <math>X</math> and <math>Y</math> be independent random variables with uniform density functions on <math>[0,1]</math>. Find <ul><li> <math>E(|X - Y|)</math>. </li> <li> <math>E(\max(X,Y))</math>. </li> <li> <math>E(\min(X,Y))</math>. </li> <...") |
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Let <math>X</math> and <math>Y</math> be independent random variables with uniform | |||
density functions on <math>[0,1]</math>. Find | density functions on <math>[0,1]</math>. Find | ||
<ul><li> <math>E(|X - Y|)</math>. | <ul style="list-style-type:lower-alpha"><li> <math>E(|X - Y|)</math>. | ||
</li> | </li> | ||
<li> <math>E(\max(X,Y))</math>. | <li> <math>E(\max(X,Y))</math>. |
Latest revision as of 21:38, 14 June 2024
Let [math]X[/math] and [math]Y[/math] be independent random variables with uniform density functions on [math][0,1][/math]. Find
- [math]E(|X - Y|)[/math].
- [math]E(\max(X,Y))[/math].
- [math]E(\min(X,Y))[/math].
- [math]E(X^2 + Y^2)[/math].
- [math]E((X + Y)^2)[/math].