# "Is P value Type I error in hypothesis testing? I'm confused about the interpretation of P value in hypothesis testing. I know that we set significance level as 0.05 which is the threshold we set for this test so that it won't suffer from Type I error by 5%. And we are comparing P to significance level, does it mean P is the probability of making type I error based on the sample?"

Is P value Type I error in hypothesis testing?
I'm confused about the interpretation of P value in hypothesis testing. I know that we set significance level as 0.05 which is the threshold we set for this test so that it won't suffer from Type I error by 5%.
And we are comparing P to significance level, does it mean P is the probability of making type I error based on the sample?
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now not quite. The p-value is calculated primarily based at the statistics we without a doubt found - it is our degree of how "uncommon" the records is, assuming that the null hypothesis is authentic (which typically corresponds to "nothing bizarre is occurring" or "the effect we're seeking to pick out isn't present" or some thing comparable).
the edge that we set, regularly written as alpha, wherein we decide that the p-price is satisfactorily "bizarre" to depend as proof in opposition to the null hypothesis, is then our chance of a type I errors - it's the possibility that, in a universe in which the null hypothesis is authentic, we get information so weird that we assume it is false.
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Chelsea Pruitt
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