Ruh Roh! If You Kick The Cuckoo Out Of The Nest, Don't Be Surprised To Find It Desecrated And Your Eggs

ruh roh! If you kick the cuckoo out of the nest, don't be surprised to find it desecrated and your eggs destroyed. In trying to protect Mira Alcor dooms her to the narrative :D

I'm curious in your interpretation, in a universe where Ian never meets Mira and Alcor how does the Bill stuff go down if it does at all?

GAH that's terrifying I love it. My one request is the laugh track is awful and Ian is the only one who can hear it. I need to point and laugh at him. He needs to be a trapped in a haunted vhs tape. It won't fix or help him but he needs it.

Ian and the twice-divorced gray-eyesed rift Ian from the first chapter of @reblogincarnation-blues's fic!

anyways the closest experience I've had to the the feeling of reading the second chapter is taking my roommate to the ER for four hours for suspected appendicitis only to come back with a UTI diagnosis and an antibiotic prescription. and it breaks your one year streak of roommates getting appendicitis. in a good way.

whole slew of ian doodles from various @reblogincarnation-blues writings!

From left to right, top to bottom:

Badass Mindscape Ian from Chapter 4 of All the Old Familiar Places

Same as 1

Very normal Bian (he's ok) from Chapter 5 of The Mirrored Heart

Soulmate AU Ian as Mira meets him in Chapter 3 of The Mirrored Heart and an older version because he survives to a happy ending and I'm giving him one (1) break (soulmark design inspired by this awesome art by @that-ghost-pal!)

pissy little baby Ian!Bill from Chapters 4 and 9 of All the Old Familiar Places

Twice divorced gray eyesed Ian (my favorite chew toy) from Chapter 1 of The Mirrored Heart

Sick of this bullshit Bian from Chapter 5 of The Mirrored Heart

This bullshit Bian from Chapter 4 of The Mirrored Heart

Okay so I saw the "shorter" and "taller" were pretty much exactly the same and I thought yeah that makes sense it's pretty surprising how much that makes sense, you pull a random sample of 2 people of different heights and the odds you pull the taller one first is the same as you pulling the shorter one first. But 10.2% (percentage at the time I'm doing this) seemed a little high for randomly pulling people that are exactly the same height. So that got me curious, assuming the tumblr population reflects the global population (which very well may not be true), what are the odds that we see at least 10.2% of the population being the same height as the person pulled right before them?

Kinda longish stats rambling under the cut so if you don't want to look at it (I'd rather you would :D) you can go right along. There is a tl;dr at the end if you just want results.

Take this with a grain of salt, I'm not sure how good my practices are. Human height is bimodal, two normal distributions, one female and one male, obviously a simplification of the human experience, but it'll do for the height distribution I'm going to use. I took the means (69 in and 64 in) and standard deviations (3 in and 2.8 in) for heights for each sex from this site, I didn't vet it but the numbers didn't seem unreasonable. It uses height data from Europe, North America, Australia, and East Asia from people born between 1886 and 1994. Looked for tumblr sex distributions and found conflicting reports so I'm just going 50/50 for simplicity. I found this site and this site suggesting it is 50/50 so hopefully I'm not too far off.

Hypothesis testing time! My hypothesis being people are more likely to actually vote on this poll if they are the same height as the prev.

I ran 10,000 simulations of pulling a random sample of 50,000 people and for each simulation recorded what percentage of people had the same height (rounded to the nearest inch) as the person pulled directly before them. Each person has a 50/50 chance of being AFAB or AMAB, and then their specific height is picked from a normal distribution based on sex. I then made a histogram for all of these simulations to visualize these results and:

WOW! that's quite far away. Pretty much 0% of these simulations had a percentage at or above 10.2%. So uh. Pretty unlikely. Pretty cool! I'd put a handful of asterisks next to this figure.

But tumblr has a reputation for being mostly female, whether or not that's true I thought it would be fun to look at a scenario where the voters here are 75/25 split female/male and a scenario where the voters are all female and all male. So here's the breakdown for these guys, I knocked the simulations down to 1,000 because I am impatient and didn't want to wait more than 2 seconds.

For all females:

Actually a decent chunk of the simulations (0.9%) make it above the 10.2% line. Still kind of unlikely but definitely not outside the realm of possibility.

For all males:

Again 0% chance of landing at or equal to 10.2% of the votes being equal height as prev! And that's just a 0.2 inch difference in standard deviation.

And my 75/25 female/male breakdown:

Also 0%. Jeez that's far.

I did one more 85/15 split just for funsies:

Still 0%. Kinda wild that introducing a little bit of sex variation changes it this much. If I'm doing something wrong conceptually, please feel free to let me know.

I'm aware that there's been a lot of change in height in the past century when the original stats were taken, so the baseline standard deviations might not be right for these purposes. Also, tumblr users tend to be concentrated in a couple countries and definitely do not reflect the real age distribution of the population. I tried looking into tumblr's country breakdown then going to the major countries' height census data but that was falling a little too deep into the rabbit hole and I don't know German. Surprisingly enough it looks like governments aren't champing at the bit to tell you the standard deviations of the heights of their populations :/.

Anyways it looks like given the very many assumptions I made about the tumblr population, there's a fighting chance that seeing your prev has the same height as you makes you more inclined to actually vote on it! (yes I'm aware correlation is not causation I just thought this was neat)

tl;dr it is pretty damn unlikely that given the tumblr population is representative of the global population, we'd see a percentage of 10.2% the same height just by random chance

Update

More votes are in! Numbers have changed! And I'm gonna do a followup on some of the previous stats I did and also some new tests! More graphs and numbers under the cut! This one's a little more text heavy and deals more with stats lingo, but I tried to keep it digestible. tl;dr at the end.

First and foremost, last test I did assuming everyone who voted in this poll was AFAB, there was an approximately 9% chance of seeing a vote for "exactly the same height" as high as we did. That vote has gone up, at the time of writing this it's 10.4%. Furthermore, the total number of votes has gone up a lot, it's around 83k at the time of writing but I rounded it up. I used the same methods to redo the simulations for an all AFAB voter group using the new conditions and voila!

Now 0% of the simulations had a proportion of the votes be exactly the same height as prev as high as we are currently seeing. There's no way to know for sure, but my preferred theory is seeing that your prev has the same height as you catches your eye and makes you more likely to vote. But for all I know, the standard deviation of heights of tumblr users is 1 inch. Can't go much further than this without rounding all of you up and measuring you >:).

Now for new stuff!

Since my last post, the gap between the taller and shorter votes has gotten bigger. At the time of writing, 44.6% of the votes are for shorter and 45% are for taller. That's only a difference of 0.4%, but on a scale of 80k+, it might mean something.

My next hypothesis is that you are less likely to vote on this poll if you are shorter than prev than if you are taller than prev.

There's a couple ways we can go about looking at this. I'll start with some of the more general ones (including same height votes) and go narrower.

Method 1: Bar Charts

Bar charts! Generally a pretty good way to visualize the distributions, but it may not be too helpful here.

On the left is what we should be seeing if all of my hypotheses (including the one about same height) are false, and you vote regardless of your height relationship to prev. The proportions here are 46.4% shorter, 7.2% the same height, and 46.4% taller. On the right is what we actually see. You can see that the same height bar is taller and can maybe see that the taller bar is slightly taller than the shorter bar, but it's pretty hard to eyeball.

At the very least we have a baseline of what the proportions should be if (given the tumblr population reflects the general population (big given here)) the likelihood of voting on this poll is independent of your height relationship with prev. This'll be my expected distribution, the good ol' aitch nought if you will.

Method 2: Chi-Square Test for Goodness of Fit

This is a good test to use to see if the distributions of categories in a sample that you are observing (y'all poll voters) matches the expected distribution of categories. I don't have a nice looking graph for this one, you basically just input your observations and expectations into a math formula, you get a number and stick that number in a graph, and the number it spits out (called the p-value) tells you how likely, in a very large number of simulations, that you get results as different from what is expected as the ones you observed, given that your hypothesis is false.

In this case, I'm just looking for if the distribution we see in our sample is likely given that the true distribution is 46.4 - 7.2 46.4. And lo and behold, my p-value was 3.4e-292. This is zero. For all intents and purposes, there is a 0% chance of seeing the results we did if all of my hypotheses are false, but we already knew this.

Method 3: Exactly the Same Thing I Did Before

Beyond this point, the actual underlying distribution of tumblr voters' heights don't matter, which is more conceptually fun for me.

This time, I redid my simulations and graphs for the percentages but using taller and shorter rather than the same height. Since the proportion of same height answers are so much higher than expected, I just factored them out completely. This left me with an expected 50/50 for what remains, and an observed 50.2/49.8 difference in taller versus shorter:

And these look pretty promising! In both cases (this makes sense, they're symmetric), only 1.3% of the simulations fell into the areas as extreme as our observations got. In the showbiz we call this statistically significant, but it doesn't win any asterisks. So it looks like this supports my hypothesis. But wait! There's one more thing we can do!

Method 4: Z-test for Proportions

Since we're just looking at two groups now, taller and shorter, we can pretty much assign a boolean flag to each observation. Let's just say that we're looking at the proportion of voters who are taller than prev. Again, we would expect this to be 50%. No fun visualizations for this one either, pretty much the same procedure as method 2 but using a different formula and different graph.

I got a p-value of 0.12. Aw shucks. In the showbiz we call this not significant and I get fired and shunned forever. Basically if we ran this simulation a whole bunch of times where voters actually were equally likely to answer "taller" as they were "shorter", in 12% of these simulations, we would see results that deviate at least as far as 50.2% voting "taller". Not that many but not enough to make any claims. I've failed you all, sorry.

SURPRISE REPLICATION CRISIS MENTION

Now, see, I could have chosen not to share that last test with all of you, and in science, a lot of the time, you wouldn't have seen this. This is because if that little number, if that p-value doesn't reach 0.05, you're not getting published. And if you're not getting published, you're not getting paid. And so there's all sorts of incentives for scientists to do a little this and a little that to their data and their experiments that end up showing you something that might not reflect what's really happening. And the only way to really tell is when other scientists try to replicate those studies (not very often because this isn't profitable), they can't get the same results.

This is a real problem in science, called the replication crisis, and in a lot of big name journals across many fields (even medical ones oh no), the number of studies that don't replicate vastly outnumber the ones that do.

Anyways I attended a talk once about ways in which we could counter the replication crisis, and for every suggestion someone made, someone else came up with a method you could use to circumvent that suggestion. People are always going to be able to find ways to wriggle their ways into filling all those requirements to get paid. This isn't to scare you from science or demonize scientists (most probably? aren't doing anything wrong), just point out that the machine is not the best.

Disclaimer: I'm not a professional, I'm just a student right now, so any number of things I said may be wrong. I could also just be lying to you and so could all the poll voters.

tl;dr

It is even more unlikely at this point that given the tumblr population is representative of the global population, we'd see a percentage of 10.4% the same height just by random chance, people are only maybe more likely to vote if they are taller than prev than if they are shorter than prev (legally I can't say), and replication crisis jumpscare!

this goes here too

@eggsistential-breakdown

IVE BEEN WORKING ON A UNIFIED THEORY IF I MAKE IT THROUGH TONIGHT EVERYBODYS GONNA HEAR ME OUT

went in a completely different direction with this i misread it and missed the "in every flashback" part. anyways i had a visceral vision of having to live in a reality where humans all of a sudden start birthing muppets and i Did Not like it

muppet adaptation of any far future TAU story like RB where in every flashback, people that lived before the transcendence are played by humans and everyone born after it is played by muppets

we never explain whether this is artistic license or supposed to literally indicate a supernatural muppetscendence occurred.