exercise:Bf1fbb9234: Difference between revisions
From Stochiki
(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> When studying certain physiological data, such as heights of fathers and sons, it is often natural to assume that these data (e.g., the heights of the fathers and the heights of the sons) are described by random variables with normal densities. T...") |
No edit summary |
||
| Line 1: | Line 1: | ||
When studying certain physiological data, such as heights of fathers and sons, it is often natural to assume that these data (e.g., the heights | |||
of the fathers and the heights of the sons) are described by random variables with normal densities. These random variables, however, are not independent but rather are correlated. For example, a two-dimensional standard normal density for correlated random variables has the form | |||
of fathers and sons, it is often natural to assume that these data (e.g., the heights | |||
of the fathers and the heights of the sons) are described by random variables with | |||
normal densities. These random variables, however, are not independent but rather | |||
are correlated. For example, a two-dimensional standard normal density for | |||
correlated random variables has the form | |||
<math display="block"> | <math display="block"> | ||
| Line 16: | Line 6: | ||
- \rho^2)}\ . | - \rho^2)}\ . | ||
</math> | </math> | ||
<ul><li> Show that <math>X</math> and <math>Y</math> each have standard normal densities. | <ul style="list-style-type:lower-alpha"><li> Show that <math>X</math> and <math>Y</math> each have standard normal densities. | ||
</li> | </li> | ||
<li> Show that the correlation of <math>X</math> and <math>Y</math> (see | <li> Show that the correlation of <math>X</math> and <math>Y</math> (see [[exercise:0a82eb3e0d |Exercise]]) is | ||
<math>\rho</math>. | <math>\rho</math>. | ||
</li> | </li> | ||
</ul> | </ul> | ||
Latest revision as of 21:45, 14 June 2024
When studying certain physiological data, such as heights of fathers and sons, it is often natural to assume that these data (e.g., the heights of the fathers and the heights of the sons) are described by random variables with normal densities. These random variables, however, are not independent but rather are correlated. For example, a two-dimensional standard normal density for correlated random variables has the form
[[math]]
f_{X,Y}(x,y) = \frac 1{2\pi\sqrt{1 - \rho^2}} \cdot e^{-(x^2 - 2\rho xy + y^2)/2(1
- \rho^2)}\ .
[[/math]]
- Show that [math]X[/math] and [math]Y[/math] each have standard normal densities.
- Show that the correlation of [math]X[/math] and [math]Y[/math] (see Exercise) is [math]\rho[/math].