They say .014(the P-Value) is a “significant number”. Says who? Why? Isn’t any number “significant” if the distribution of data points is mostly around that area?
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The p-value is the probability that if there were a parallel universe with everything the same and the experimental variables you’re altering do nothing at all, then in that parallel universe you’d get a signal the size of the one you’re looking at or bigger.
5% is considered close enough to go have a better look. 1% means you might well be onto something. 0.05% means you probably have something. You can keep going.
These numbers are chosen because of how random numbers behave. The sum of a huge number of completely random numbers that don’t have anything to do with each other is normally distributed. The fewer reasons your data truly is the way it is, and the more those reasons depend on each other – or if they multiply rather than add – your random number stops being normal and you should use different stats to work out whether the thing looks true or not.
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