Yes, it means could be the same, not are the same. It does mean they are confident (95% confident, I assume, I’m not clicking through to the study) that the rates are different for men and women in Gen X
It does mean they are confident that the rates are different for men and women in Gen X
Umm, surely not? If the confidence intervals overlap it means that they are not confident that the rates are different, doesn’t it? Of course, it also does not mean that they can say they are confident that the reading rates are the same.
So the statistically sound way of saying it is that the null hypothesis is that reading rates are the same, and their study has failed to reject the null hypothesis.
If you want to be precise, overlapping intervals mean that we lack evidence to assert that the means are statistically different for our chosen confidence level. This is often simplified to the statement that they are statistically the same.
Yes, it means could be the same, not are the same. It does mean they are confident (95% confident, I assume, I’m not clicking through to the study) that the rates are different for men and women in Gen X
Umm, surely not? If the confidence intervals overlap it means that they are not confident that the rates are different, doesn’t it? Of course, it also does not mean that they can say they are confident that the reading rates are the same.
So the statistically sound way of saying it is that the null hypothesis is that reading rates are the same, and their study has failed to reject the null hypothesis.
Gen X is the only category for which the CIs don’t overlap at all
Oh right I see, sorry.
If you want to be precise, overlapping intervals mean that we lack evidence to assert that the means are statistically different for our chosen confidence level. This is often simplified to the statement that they are statistically the same.