Solution

Past exam of the mathematics course of the University of Cambridge / 2003 / iii / Paper 29 / 4 / a / Solution

Past exam of the mathematics course of the University of Cambridge / 2003 / iii / Paper 29 / 5 / Solution

Past exam of the mathematics course of the University of Cambridge / 2003 / iii / Paper 32 / 5 / Solution

Past exam of the mathematics course of the University of Cambridge / 2003 / iii / Paper 33 / 1 / c / Solution

Past exam of the mathematics course of the University of Cambridge / 2003 / iii / Paper 33 / 2 / b / Solution

Past exam of the mathematics course of the University of Cambridge / 2003 / iii / Paper 43 / 3 / a / i / Solution

Past exam of the mathematics course of the University of Cambridge / 2003 / iii / Paper 43 / 4 / Solution

Past exam of the mathematics course of the University of Cambridge / 2003 / iii / Paper 79 / 1 / d / Solution

Past exam of the mathematics course of the University of Cambridge / 2004 / iii / Paper 30 / 6 / c / Solution

Past exam of the mathematics course of the University of Cambridge / 2004 / iii / Paper 34 / 3 / Solution

Past exam of the mathematics course of the University of Cambridge / 2004 / iii / Paper 34 / 6 / Solution

Past exam of the mathematics course of the University of Cambridge / 2004 / iii / Paper 35 / 4 / b / Solution

Past exam of the mathematics course of the University of Cambridge / 2004 / iii / Paper 37 / 3 / Solution

Past exam of the mathematics course of the University of Cambridge / 2004 / iii / Paper 40 / 5 / iv / Solution

Past exam of the mathematics course of the University of Cambridge / 2004 / iii / Paper 43 / 1 / ii / Solution

Past exam of the mathematics course of the University of Cambridge / 2004 / iii / Paper 43 / 5 / ii / Solution

Past exam of the mathematics course of the University of Cambridge / 2004 / iii / Paper 67 / 2 / d / Solution

Past exam of the mathematics course of the University of Cambridge / 2005 / ia / Paper 2 / 11F / 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