> They found that out of 100,000 non-drinkers, 914 would develop an alcohol-related health problem such as cancer or suffer an injury.
That sentence is ... what? How do you suffer alcohol related injury without drinking?
That sentence is ... what? How do you suffer alcohol related injury without drinking?
So 914 vs 918 out of 100,000? That's gotta be below statistical significance.
914 to 918 per 100,000 is a tiny change. It might be caused by subtle differences in the two groups that have nothing to do with alcohol. If anything, the study shows that having <= 1 drink a day is basically the same as being a teetotaler.
Two drinks a day, OTOH, are visibly worse for health (914 to 977).
A bit more rigorous would be to compare maybe the Beta distribution with a=915 to a=919 and b=100,000 in both cases. Or Poisson distributions with lambda 914/100,000 and 918/100,000.
I don't know whether Beta or Poisson are better fits. I don't even know how I'd find out.
Abd of course, that's still a fairly handwavy approach and I'd love for someone to show me how it's done for real.
But just saying it's noise without quantifying it seems to me exactly as misleading and irresponsible as the original news, only biased in the other direction.
Then there are subtle things such as "how many people in group A vs group B live next to a motorway or suffer from higher levels of ambient noise". Not to mention the cultural differences (religious fasting or absence thereof etc.)
Picking up huge groups of people that are perfectly equivalent is very, very hard.
But I am not a professional either. I studied algebra, not statistics, we only had a year-long course in the basics. Maybe I was too handwavy.
Perhaps, as comrade Upton Sinclair put it, "It is difficult to get a man to understand something, when his salary depends on his not understanding it."
You can reject a null hypothesis with statistical significance even if the effect size of the alternate hypothesis is small -- you just need a big sample.
At a sample size of 20million that's 182.800 cases in the non-alcoholic group and 183.600 in the alcoholic once a day group. At that scale I wouldn't trust my data enough to believe the reporting of once-a-day and not-at-all is actually accurate and other completly unrelated unaccounted effects do not outweigh my testesd criteria.
If I haven't done any major errors calculating this (which might be, because it's back of the napkin math with a t-test calculator or my assumptions are wrong), I doubt the sample size and accuracy of the measure is high enough to make a statistical significant claim about these groups.
Even if it actually is a somewhat accurate result, it means having one drink per day increases health issues by as little as 0.5%. The risk of addicition and starting to drink much more probably heavily outweighs that.
Regarding OPs statement, I think it's fair to assume what is usually meant is "that has to be statistically insignificant for any sample size this sutdy probably had".
The actual conclusion from the actual paper is "the level of consumption that minimises health loss is zero"
I’ll take my downvotes now.