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.