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Argh.


Nanuq

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It seems that it's an endless wait for my new watch to arrive in the mail. But on second thought... is it really?

The cumulative distribution function of the normal distribution is expressed in terms of the density function as follows:

300926-2341.png

where the standard normal cdf Φ is just the general cdf evaluated with μ = 0 and σ = 1:

300926-2342.png

The standard normal cdf can be expressed in terms of a special function called the error function, as

300926-2343.png

and the cdf itself can hence be expressed as

300926-2344.png

The inverse standard normal cumulative distribution function, or quantile function, can be expressed in terms of the inverse error function:

300926-2345.png

and the inverse cumulative distribution function can hence be expressed as

300926-2346.png

For large x the standard normal cdf is close to 1 and is close to 0. The elementary bounds

300926-2347.png

in terms of the density are useful. Using the substitution v = u2/2, the upper bound is derived as follows:

300926-2348.png

Similarly, using and the quotient rule,

300926-2349.png

Solving for 300926-2350.png provides the lower bound.

Meaning... it will get here when it gets here. :huh:

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