Gerold,

Yes, you got the gist of the experiment right.

Regarding Allen's question, we also allowed participants to choose any estimation method they desired, to find out if the anchoring effect was stronger for some techniques. It seemed that participants were equally biased by the effect, no matter which method they chose.

paper at
http://www.cs.toronto.edu/~jaranda/pubs/MScThesis-JorgeAranda.pdf

That's my M.Sc. thesis based on the same topic. For a far more exciting read, you can instead find the ESEC/FSE paper here:

http://www.cs.toronto.edu/~jaranda/pubs/AnchoringAdjustment.pdf

Finally, Magne Jorgensen, at the Simula Research Lab, has been doing a lot of interesting research on expert-based estimation that should be relevant to Allen's question too.

Thanks,
Jorge

presentation at
http://www.cs.toronto.edu/~jaranda/pubs/Presentation-AnchoringAdjustment-Feb05.pdf
to the best of my knowledge the idea of the experiment was to include some minor expected duration information (an "anchor") into a document
that was the basis for an estimation.
in the experiment the estimators got heavily biased by this anchor. best regards, gerold

    -----Ursprüngliche Nachricht-----
    *Von:* [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
    Auftrag von *janice singer
    *Gesendet:* Montag, 22. Januar 2007 01:24
    *An:* [EMAIL PROTECTED]; discuss@ppig.org
    *Betreff:* Re: PPIG discuss: software estimating and partitioning

    Jorge Aranda, a grad student at Utoronto did an excellent study on
    software estimation.

    J. Aranda and S. M. Easterbrook (2005) Anchoring and Adjustment in
    Software Estimation. European Software Engineering Conference / ACM
    SIGSOFT Symposium on the Foundations of Software Engineering
    (ESEC/FSE'05), Lisbon, Portugal, Sept 5-9, 2005.

    Janice


    On 1/21/07 5:23 PM, "[EMAIL PROTECTED]" <[EMAIL PROTECTED]> wrote:

        A key aspect of programming in practice is the reliable
        estimation of size, time and effort.  It seems like most people
        that are good at estimating do so by partitioning the problem
        into smaller pieces that can be handled more easily.  Then,
        final estimates are accomplished by combining the pieces.  This
        procedure is certainly what engineering approaches teach and I
        think other approaches as well.
But I haven't been able to find much empirical data suggesting
        that software estimation done by partitioning is superior to
        that done more "wholistically".  I assume that I am missing
        something huge and obvious since partitioning is such an
        important cognitive tool (and has been for such a long time).
        But, I haven't found empirical references yet
Can anybody direct me to references on this topic. Thanks very much Dr. Allen Milewski
        Department of Software Engineering
        Monmouth University
        [EMAIL PROTECTED]
        --




--
    Janice Singer, PhD

    NRC Institute for Information Technology | Institut de technologie
    de l'information du CNRC

    Tel/Tél: (613) 993-7760| Facsimile/télécopieur: (613) 952-7151

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    ON K1A 0R6

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