--Hi,
p-value = 0.01 and p-value = 0.012
is it risky to say that it is the same thing in terms of probability ?
p=0.01 --> * *
p=0.012 (p>0.01) --> *
Thank you --
Strictly speaking, 1% is not the exact same thing as 1.2% but "practically" it probably makes no difference for any reasonable conclusions about "statistical significance." The "*" guidelines are arbitrary anyway.
Most importantly, the precision of most sample estimates of probability (p value) is probably not that high. Sampling error may account for the "difference" between .010 and .012. Also, assumptions underlying statistical tests of significance are often at least in part violated in practice so that the precision of the p value estimate is often questionable.
Not sure if I understand your question, but the answer is .002. I don't understand what your stars are, but if you are using different numbers of them to denote something, you shouldn't.
You probably don't want to say something about "probability" based on the p-values. This will probably lead to making confusing or unhelpful claims. ... In the cases of p = 0.010 and p = 0.012, you have good evidence to reject the null hypothesis. (If that's the way you are using the p-value). If you are using the p-value to indicate the strength of a claim, you might just say that these p-values are "similar", or something. ... In any case, be sure to look at the effect size and the practical importance of the results. ... There's nothing to be gained by making any conclusions based on the difference between p = 0.010 and p = 0.012.