I’d be curious what constitution a group a versus a group b and how you get 2 billion of them.
But I’ll interpret it as sperm on a race track since you can get 2 billion runs with one nut.
I have to say after billion trials the averages that you calculate did come from random sample, but it would be indicative average for that group since it can’t move far from that calculated average.
I’m visualizing the 2 billion points of both groups and seeing a bell curve with a lot of overlap. I guess they would be different, but overall very similar since the variance is pretty wide.
Right. But that’s what p-values quantify: given the number of trials and the observed variance and means, how likely is it that the two groups are drawn from the same distribution versus actually having different means?
So variance isn’t “more important” than p-values; high variance means that (by definition) your p-value is lower (less confident) than it otherwise would be.
I’d be curious what constitution a group a versus a group b and how you get 2 billion of them.
But I’ll interpret it as sperm on a race track since you can get 2 billion runs with one nut.
I have to say after billion trials the averages that you calculate did come from random sample, but it would be indicative average for that group since it can’t move far from that calculated average.
I’m visualizing the 2 billion points of both groups and seeing a bell curve with a lot of overlap. I guess they would be different, but overall very similar since the variance is pretty wide.
Right. But that’s what p-values quantify: given the number of trials and the observed variance and means, how likely is it that the two groups are drawn from the same distribution versus actually having different means?
So variance isn’t “more important” than p-values; high variance means that (by definition) your p-value is lower (less confident) than it otherwise would be.