The sample size was in the tens of thousands (39K total cases according to the original EUSEM article) so it would be extremely surprising if there were no real difference. You could easily say it’s within margin of error if there were only a few hundred cases but we’re talking about tens of thousands here.
Important to note though that the data only accounted for Canada and the US.
Meh… Even without seeing the data collection methodology, or the analysis, I’m calling shenanigans. Thats an almost non-existent difference - how do we know the cases where women didn’t get support are primarily women-only spaces (say women’s gym, yoga, etc)?
Someone’s using this slight difference to push a narrative.
Having a larger sample size doesn’t necessarily decrease the margin of error. It’s impossible to say if the difference is statistically significant without crunching the numbers.
It is still a sample, which is therefore subject to a margin of error. Unless you think this data accounts for all CPR given anywhere to anyone, ever.
For example, if they’d only sampled one man and one woman, and the man reported receiving CPR and the woman reported not, the “study” would show 100% of men and 0% of women receive CPR. Staggering “real-life numbers”!
I’m aware. My point is that “real life numbers” still have margins of error. The person to whom I’m responding implied that “real life numbers” aren’t subject to a margin of error.
52% versus 55%. 61% vs 68% in public places. Not a lot of difference, within margin of error even.
The sample size was in the tens of thousands (39K total cases according to the original EUSEM article) so it would be extremely surprising if there were no real difference. You could easily say it’s within margin of error if there were only a few hundred cases but we’re talking about tens of thousands here.
Important to note though that the data only accounted for Canada and the US.
Meh… Even without seeing the data collection methodology, or the analysis, I’m calling shenanigans. Thats an almost non-existent difference - how do we know the cases where women didn’t get support are primarily women-only spaces (say women’s gym, yoga, etc)?
Someone’s using this slight difference to push a narrative.
Having a larger sample size doesn’t necessarily decrease the margin of error. It’s impossible to say if the difference is statistically significant without crunching the numbers.
What do you mean by “margin of error”?
https://en.m.wikipedia.org/wiki/Margin_of_error
This isn’t a pole. This isn’t self reported numbers. Those are real life numbers
It is still a sample, which is therefore subject to a margin of error. Unless you think this data accounts for all CPR given anywhere to anyone, ever.
For example, if they’d only sampled one man and one woman, and the man reported receiving CPR and the woman reported not, the “study” would show 100% of men and 0% of women receive CPR. Staggering “real-life numbers”!
All of science is just a sample. Population trends can be observed in smaller subsets.
I’m aware. My point is that “real life numbers” still have margins of error. The person to whom I’m responding implied that “real life numbers” aren’t subject to a margin of error.