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Big Bang finding challenged

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Re: Big Bang finding challenged

#11
post #6
post #3

Earlier quoted context omitted.

Not just one. This has been mounting for a while: http://resonaances.blogspot.se/2014/05/is-bicep-wrong.html http://resonaances.blogspot.se/2014/05/follow-up-on-bicep.ht... http://resonaances.blogspot.se/2014/05/weekend-plot-bicep-li... Note also Steinhardt's opinon piece: http://www.nature.com/news/big-bang-blunder-bursts-the-multi...

> " Not just one. " But you linked to random blogspot articles, and Steinhardt is the guy who the first source is referencing. His name is mentioned in the byline. He's the guy from Princeton I mentioned. All of this is mainly coming from him, and those blogs you linked are the result of his statements (aka opinion sprawl).

The "random blog posts" are by Adam Falkowski, a particle physicist who has been following the controversy over BICEP2 from the start. They document how opinion has been swinging over time.

Steinhardt is not "the guy who the first source is referencing". The two references in the first source are

1) http://arxiv.org/abs/1405.5857 , by Mortonson and Seljak, both at LBNL and UC

2) http://arxiv.org/abs/1405.7351 , by Faluger, Hill and Spergel, from IAS, NYU and Princeton, respectively.

As you may have noticed, none of them is Steinhardt.

Re: Big Bang finding challenged

#12
post #10

Earlier quoted context omitted.

With the original announcement came a "five sigma" or so claim. Was that misleading or not? (was it plain wrong?) I mean, I'd expect from hearing something like that that unless the underlying theory changes the hypothesis is almost certainly true. Or is the uncertainty figure given in a more limited sense?

If you are making a systematic mistake (not necessarily an error, could also be an approximation that doesn't hold) in your analysis, the "5sigma" does not really take that into account. Struggling to come up with a simple example. Imagine you collect some data, analyse it and see a "3sigma" effect. You decide to collect more data to see if the effect keeps getting bigger or goes away. After collecting a lot more dat…

I suppose if your estimator is biased and not consistent -- due to some sort of omitted variable -- you can end up with "significant" estimates that are completely removed from reality. Great explanation at http://eranraviv.com/blog/bias-vs-consistency/.
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