Density dependent PVA in excel 08

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

Info icon This preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon
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.
Image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
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 .
Image of page 2
Image of page 3
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern