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While there are many reasons why an experiment might be irreproducible, sometimes it is because of the fact that there was never really anything there in the first place. There are a variety of ways to analyze data that might lead an experimenter to decide the results are statistically significant when they actually are not.

A great introduction to this topic was produced by the crew over at Veritasium. While the discussion does get a little heavier on the math at times, the topic of ‘P-Hacking’ is introduced. P-Hacking occurs when researchers examine their data in specific ways that might lead to a higher chance of getting a ‘good’ result even when the data may not support it.

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TED-Ed
Lesson Creator
New York, NY
Reproducibility is not a new concern. Paraphrased from a few years back; a famous scientist lamented, “This might surprise as much as dishearten, but you will meet with experiments which may, upon further trial, disappoint your expectation… either not at all succeeding constantly, or at least varying much from what you expected.” Who said this? The famous Irish scientist Robert Boyle… in 1673.
12/05/2016 • 
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