Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 31 / 4 / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 33 / 2 / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 33 / 3 / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 36 / 3 / b / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 36 / 3 / d / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 36 / 4 / c / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 36 / 4 / g / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 37 / 4 / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 38 / 1 / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 38 / 4 / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 39 / 4 / i / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / iii / Paper 62 / 2 / b / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / ii / Paper 1 / 13I / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / ii / Paper 1 / 29J / c / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / ii / Paper 3 / 27I / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / ii / Paper 3 / 5I / Solution

Past exam of the mathematics course of the University of Cambridge / 2009 / ii / Paper 4 / 29J / 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

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 Incoming links: Normal distribution