666
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
this post was submitted on 28 Mar 2026
666 points (98.7% liked)
You Should Know
45131 readers
33 users here now
YSK - for all the things that can make your life easier!
The rules for posting and commenting, besides the rules defined here for lemmy.world, are as follows:
Rules (interactive)
Rule 1- All posts must begin with YSK.
All posts must begin with YSK. If you're a Mastodon user, then include YSK after @youshouldknow. This is a community to share tips and tricks that will help you improve your life.
Rule 2- Your post body text must include the reason "Why" YSK:
**In your post's text body, you must include the reason "Why" YSK: It’s helpful for readability, and informs readers about the importance of the content. **
Rule 3- Do not seek mental, medical and professional help here.
Do not seek mental, medical and professional help here. Breaking this rule will not get you or your post removed, but it will put you at risk, and possibly in danger.
Rule 4- No self promotion or upvote-farming of any kind.
That's it.
Rule 5- No baiting or sealioning or promoting an agenda.
Posts and comments which, instead of being of an innocuous nature, are specifically intended (based on reports and in the opinion of our crack moderation team) to bait users into ideological wars on charged political topics will be removed and the authors warned - or banned - depending on severity.
Rule 6- Regarding non-YSK posts.
Provided it is about the community itself, you may post non-YSK posts using the [META] tag on your post title.
Rule 7- You can't harass or disturb other members.
If you harass or discriminate against any individual member, you will be removed.
If you are a member, sympathizer or a resemblant of a movement that is known to largely hate, mock, discriminate against, and/or want to take lives of a group of people and you were provably vocal about your hate, then you will be banned on sight.
For further explanation, clarification and feedback about this rule, you may follow this link.
Rule 8- All comments should try to stay relevant to their parent content.
Rule 9- Reposts from other platforms are not allowed.
Let everyone have their own content.
Rule 10- The majority of bots aren't allowed to participate here.
Unless included in our Whitelist for Bots, your bot will not be allowed to participate in this community. To have your bot whitelisted, please contact the moderators for a short review.
Rule 11- Posts must actually be true: Disiniformation, trolling, and being misleading will not be tolerated. Repeated or egregious attempts will earn you a ban. This also applies to filing reports: If you continually file false reports YOU WILL BE BANNED! We can see who reports what, and shenanigans will not be tolerated. We are not here to ban people who said something you don't like.
If you file a report, include what specific rule is being violated and how.
Partnered Communities:
You can view our partnered communities list by following this link. To partner with our community and be included, you are free to message the moderators or comment on a pinned post.
Community Moderation
For inquiry on becoming a moderator of this community, you may comment on the pinned post of the time, or simply shoot a message to the current moderators.
Credits
Our icon(masterpiece) was made by @clen15!
founded 2 years ago
MODERATORS
and 90% of statistics are made up
I'm a data analyst. A significant part of any statistic is selecting the dataset to aggregate over, which often means filtering it down to the subset you're interested in, and responsible analysis has to be aware of the bias that introduces.
Suppose you're tracking delivery times. If I calculate the average time from order to delivery for orders placed in the last week, none of the orders will have a delivery time greater than one week. I've had to argue why we should use the orders delivered last week instead.
On the other hand, if a set of orders is delayed, we won't immediately see that spike in turnaround time until they actually get delivered, so we need to separately track and compare the amount of open orders and their respective age at the start of the week to put the turnaround time in context.
The problem I see with many statistics online, particularly ones just reposted somewhere else as summary, is intransparency about the criteria for selecting and aggregating the data, the impact of context and the bias resulting from both.
Every statistic is skewed in some way, but without explaining how and why, it's easy to misunderstand (or even misrepresent) them.
In essence: 90% of statistics are worthless. Even if not made up, they might as well be.
(That one definitely is made up though.)