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In a recent episode of the Big Picture Science podcast, there was an interview with Stuart Firestein (chair of the Columbia University Biology Department) in which he discussed his book Ignorance: How It Drives Science. In particular, he mentioned that for the most part he dislikes hypotheses---they tend to pigeonhole people's idea of what "good data" is, so that if when unexpected happens, it's often thrown out as "bad data".

Is this a problem in physics? If so, how much of a problem is it, and what, if anything, do physicists do to attempt to mitigate it?

My instinct tells me that this is a problem, albeit possibly not as much as in so-called "soft" fields such as psychology and sociology where eliminating variables and bias is much more difficult (at least I assume it's much more difficult).

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It's all part and parcel of science. If we didn't have hypotheses and conjecture... –  raindrop Feb 1 '13 at 16:59
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Unlike the case in psychology and sociology, in physics we are capable of repeating the same experiment/measurement in the same conditions over and over. Any valuable, unexpected results that reflect reality should repeat also, so there is no such problem.

This is true unless the experiment is not repeated enough to filter unexpected results out of noise. This is why the LHC collides particles over and over, to catch any such repeated unexpected events over the background noise with big certainty.

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