p-value refers to the probability of making a type I error (probability of having a false positive). When the 95% confidence interval does not include the null value (1 for ratio, 0 for difference), 0 < p < 0.05 (between 0% and 5% chance of having a false positive). However, when the 95% confidence interval includes the null value, 0.05 < p < 1.0 (between 5% and 100% chance of having a false positive).
Think of it as follows ---> If the 95% confidence interval includes the null value, then you have somewhere between 5% and 100% chance of being wrong if you conclude it is right. Conversely, if the 95% confidence interval does not include the null value, then you have between 0% and 5% chance of being wrong if you conclude that is is right
submitted by stapes2big(4), 2019-05-20T03:01:10Z
I’m not sure about this one but the way I thought about it was that since the confidence interval included 1, it was not significant. And thus p value must be above
0.05