Density dependent PVA in excel 08

# Density dependent PVA in excel 08 - Random numbers and...

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Random numbers and stochastic simulations in Excel Functions in bold type require that PopTools be installed. When a PopTools function duplicates one of Excel’s built-in functions, the PopTools function is often easier to read and remember and is also based on algorithms that are more numerically robust. To generate a new set of random numbers, hit the ‘F9’ key. This replaces all the random numbers in the worksheet and updates any other calculations that depend on them. Functions for generating random numbers These are the distributions that you will most commonly be using in this class. There are a variety of other distributions available, both in Excel and PopTools, which use similar syntax. In the “Paste Function” dialog box, look under either “Statistical” or “PopTools random variables” to see what’s available. Continuous distributions RAND() Returns a pseudo-random number uniformly distributed between 0 and 1. Either implicitly or explicitly, this is the basis for all the other built-in random number functions. dRandReal( l , u ) Returns a pseudo-random number that is uniformly distributed between l and u . This is the basis (although you never see it) for all the other PopTools random number functions. NORMINV(RAND(), m , s ) Returns a pseudo-random number that is normally distributed with mean m and standard deviation s . dNormalDev( m , s ) Returns a pseudo-random number that is normally distributed with mean m and standard deviation s . LNORMINV(RAND(), m , s ) Returns a pseudo-random number that is log-normally distributed with mean m and standard deviation s . dLogNormalDev( m , s ) Returns a pseudo-random number that is log-normally distributed with mean m and standard deviation s . BETINV(RAND(), m , s , l , u ) Returns a pseudo-random number that is beta distributed with mean m and standard deviation s , and bounded between l and u (the beta distribution has a central tendency, like the normal, but only a finite range of allowable values; it is often used with l = 0 and u = 1). dBetaDev( m , s ) Returns a pseudo-random number that is beta distributed with mean m and standard deviation s , and bounded between zero and one.

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Discrete distributions BINOMINV(RAND(), N , p ) Returns a pseudo-random number that is binomially distributed with sample size N and success probability p . dBinomialDev( N , p ) Returns a pseudo-random number that is binomially distributed with sample size N and success probability p .
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