Even if you were right and this were relevant, this would not be a statistical anomaly, it would be a methodology failure
Even if you were right and this were relevant, this would not be a statistical anomaly, it would be a methodology failure
Maybe you should try posting more often then ;)
Medic mains when their “useless” ubersaw crits for the 12th time in a row
Your carrier pigeon is doing some serious work today
Oh, it’s not partisan? That’s… fine, yeah
Any church that does this should not get to be tax-free under the religious exemptions, because they’re also a political organization
Especially when it isn’t even using its vs it’s properly
I’m confused, are you asking to replace “you”/“your” with “it”/“its”? That’s the only pronoun there but I’ve never seen it be replaced and it’s not really gramatically equivalent.
TIL the scope of a conversation can never include anything that wasn’t in the original post. I can’t imagine how boring your conversations must be irl.
Womp womp
I refuse to upvote any post woth the word “slammed” in the title
Hi it’s the music police, your taste is criminal
If you delete Banana Pancakes I’m deleting your spine
It would be pretty funny if nobody could make a song that’s 4 min 33 sec long again though so 4’33" might be funnier
I choose this comment as my song to delete
Yeah, at least that other “product of its time” ™ song about being surprised someone at the bar is trans sounds decent. Dude Looks Like a Lady is just bad.
I want the retail stores to play something with more gusto, like I Believe in Father Christmas (by Greg Lake, sounds a bit different than the name suggests)
Peter Pan is a very weird movie. Peter himself is pretty questionable.
Sorry, I think you need to brush up on statistics. The relevant measurement here would be the variance (Variation? Variability? Whatever the term is officially called) in the relevant statistic, not the size of the statistic itself. Using the variance and previous average of the deaths per capita statistic, you can calculate the likelihood of the current deaths per capita having this value compared to the past values. If that likelihood is sufficiently low (for most scientific fields, 5% or less), the result is declared significant, since it’s different than what we would expect it to be if nothing had changed, and we can say that with a high (>95%) confidence. To learn more about this “predict the chance of the result being within normal bounds and then go “whoa that’s weird” when it’s not” method, look up “null hypothesis”, or even better “statistical significance”.
To give a practical example: The number or deaths from car accidents is fairly low per capita, but since we have a very large amount of data available, it has a low variance and we can predict and calculate the ratio very accurately. If you look up a graph of car deaths per capita over time, each year will only have a ratio of like 0.001%, but the variance between years will not be very high, because we have so much data that the little bits of randomness all even out. We can then look at, for example, car deaths per capita for streets with crosswalks vs without crosswalks, and even though they’ll both be a fraction of a percent, because they’re both measured so accurately we can make confident assessments of that data.