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"Sadly, the concept of p-values and significance testing forms the very core of statistics. A number of us have been pointing out for decades that p-values are at best underinformative and often misleading. Almost all statisticians agree on this, yet they all continue to use it and, worse, teach it. I recall a few years ago, when Frank Harrell and I suggested that R place less emphasis on p-values in its output, there was solid pushback. One can’t blame the pusherbackers, though, as the use of p-values is so completely entrenched that R would not be serving its users well with such a radical move.

And yet, wonder of wonders, the American Statistical Association has finally taken a position against p-values. I never thought this would happen in my lifetime, or in anyone else’s, for that matter, but I say, Hooray for the ASA!"

https://matloff.wordpress.com/2016/03/07/after-150-years-the-asa-says-no-to-p-values/

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What is the big/major difference between margin of error and confidence interval?
Why we need to set margin of error if we have already set confidence interval at (- +)2SD ?

Note: Kindly help I am so confused, I need conceptual answers, not google ones!

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"Suppose I tell you that I know of a magician, The Amazing Significo, with extraordinary powers. He can undertake to deal you a five-card poker hand which has three cards with the same number.
You open a fresh pack of cards, shuffle the pack and watch him carefully. The Amazing Significo deals you five cards and you find that you do indeed have three of a kind." #pHacking

http://deevybee.blogspot.co.uk/2016/01/the-amazing-significo-why-researchers.html

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The reproducibility crisis in conventional statistics is growing. Here is a recent study of a failure to replicate a finding, the romantic priming effect.

http://blogs.discovermagazine.com/neuroskeptic/2015/11/10/reproducibility-crisis-the-plot-thickens/#.VncFaOjRaf0

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