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Understanding criticisms of a paper

  1. Apr 9, 2010 #1
    First up apologies if this is a violation of a rule or COC.

    Anyway new paper was published a couple of days ago concerning first flowering dates of flowers in the UK.

    http://rspb.royalsocietypublishing.org/content/early/2010/04/01/rspb.2010.0291.full" [Broken]

    A report on it was published in the http://www.guardian.co.uk/environme...-study-shows?showallcomments=true#comment-51".
    And as always a somewhat exuberant discussion broke out. In the end one comentator made this criticism of the paper.

    Now I understand that 2 standard deviations are a confidence interval of 95%. I was very wary however of the suggestion that this was all "accounted for solely by chance variation" even at less than 95% confidence surely that is not just chance, just less likely not to be chance?

    I emailed the author and they very kindly responded, although again I lack the skills to fully understand their response. They said I could use the response but not cut and paste it, which I am very happy to comply with. The author infromed me that they do not simply apply an average for the estimated indices but apply a hierarchical Bayesian model that in their words can "estimate parameters with uncertainties in the estimate".

    I dont quite follow what that means, I understand the baysian statistics are a means of reducing the randomness in statistics. (My ex does this for a living and I am going have her go through it with me hopefully but thought I would also ask here). The phrase that the author used that has me foxed is this one: "estimate parameters with uncertainties in the estimate". Can someone explain what that means and what the result would be?

    As I said apologies if people do not think this is what the forum is for, but I keep seeing things like baysian methods being mentioned all over the place and am never quite sure about it.
    Last edited by a moderator: May 4, 2017
  2. jcsd
  3. Apr 9, 2010 #2


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  4. Apr 10, 2010 #3
    Hmm I read:

    How many people were that 50 years ago, 100 years ago? Etc. Is there a chance that the first flowering date is biased by the number of observers? Like, the more of them, the lesser the chance that any earlier flower goes unnoticed.
  5. Apr 10, 2010 #4


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    If we had information about how many noticed a flower by a given date, we could probably undo that bias...
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