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> This is the same misconception I have been trying to dispel. The null hypothesis is not the inverse of that "layman's" statement, it is a specific set of pred
by ihnorton 10y ago
> This is the same misconception I have been trying to dispel. The null hypothesis is not the inverse of that "layman's" statement, it is a specific set of predicted results calculated in a very specific way.
The entire point of this discussion is that the software is not calculating the null hypothesis that users expect. That the current model it does in fact calculate is internally-consistent is tautological and irrelevant (though actual bugs were found in at least one package).
As you yourself said: "I didn't read the code, or even the paper very closely." (https://news.ycombinator.com/item?id=12037207 https://news.ycombinator.com/item?id=12037207) Perhaps you should do?
- nonbel 10y agoThere really is no reason for me to read the paper closely. They say that the null hypothesis is wrong, and they know exactly why. Then, like multiple people responding to me here, they also want to say somehow the null hypothesis is true. Everyone who has questioned me also does admit there is something wrong with that hypothesis they tested. You do it too: "the software is not calculating the null hypothesis that users expect", but then you also want to say the null hypothesis they tested is true! Just bizarre, what underlying confusion is making people repeat something clearly incorrect? The null hypothesis cannot be both true and false at the same time. There is a big difference between a "positive" result that is a "false positive" and a "positive" result due to a false null hypothesis. This is a clear cut case of the second.