Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 34 / 1 / d / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 34 / 3 / b / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 35 / 3 / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 36 / 1 / b / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 36 / 1 / c / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 41 / 1 / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 41 / 3 / iii / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 41 / 3 / i / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 42 / 3 / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 42 / 6 / ii / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 43 / 2 / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 44 / 4 / c / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 47 / 1 / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 47 / 2 / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 47 / 3 / b / iii / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 47 / 3 / b / i / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / iii / Paper 47 / 6 / Solution

{title2=$N(\mu,\sigma^2)$}
{wiki}

= Gaussian
{c}
{synonym}

= Normal
{synonym}

= Gaussian distribution
{c}
{synonym}

= Normally distributed
{synonym}

The normal distribution has density proportional to $\exp(-(x-\mu)^2/(2\sigma^2))$.


Normal distribution

Codex @codex  0

 Incoming links: Normal distribution