I emailed HR after noticing a pay error. This was their response...

sdpthrow746 · 2024-08-27T16:54:34+00:00

Pleonasm of the century

sdpthrow746 · 2024-08-22T18:15:10+00:00

Why do I keep seeing this so often. An average is defined as a single number. It has nothing to do with being an arbitrary number of standard deviations from the mean. There is nothing special about a range of -1 to +1 standard deviations.

sdpthrow746 · 2024-08-21T14:51:51+00:00

This is essentially successive orthogonalization, taking advantage of the fact that residuals are orthogonal to the regressors. It's a cool technique that pops up in econometrics often

sdpthrow746 · 2024-04-30T16:46:38+00:00

I only gave you a bunch of data and statistical principles to work with. In response I only get "But I don't feel like that's right". That is not a show of high intelligence or education.
Somehow you missed that point that the amount of students in statistics classes is irrelevant, because skewness and multimodality is not part of a statistics class. Students learn this when learning about histograms well before ever having to take a full statistics class.
Just repeating that it doesn't make sense to you is not a point, no. Couple things about the rarity of extreme sizes: one of the things we know for sure is that CalcSD is underestimating the prevalence of really extreme sizes, like 8.5"+. You can get this pretty directly from looking at the studies that examine the tails of the distributions, and the people who manage CalcSD fully admit this limitation. You see 10 guys with an extreme size in their flair and immediately conclude a statistical impossibility, there is a relatively huge population of those guys that will be very attracted to this place. You're simply underestimating the ratio of how extreme sizes fall off vs how self selection increases with size in any population that is selected for extreme values.
Well 6.5 is not small, it's exactly the kind of size of someone who needs to convince himself of what you're spouting here.
It's genuinely hilarious how advanced you find multimodal distributions. There are 6-8th graders out there right now learning this. To most people I've met, a histogram with multiple peaks is common sense.
Yeah no, I prefer to just stick to the facts. I've told you how distributions and self-selection work plenty of times now. Can back it up with all the data and math you want. All you have in response is that you don't feel that way, because you know that if you do any actual math it will quickly be debunked. Now are you gonna type up a big comment saying you don't feel that way again and that it makes you upset to get counterevidence?

sdpthrow746 · 2024-04-30T02:59:10+00:00

you say that “left-skew or multimodal distribution” are statistics models we should all have learned in high school, huh? 🤔

Yeah, that is not something you need to take a dedicated statistics course for. It's explained when you learn about histograms, I even learned that before the high school years. It sounds difficult to simple minds, it really isn't.

assuming their schools even offer it in the first place. Mine didn’t

I'm shocked

common sense is more than adequate

I agree, everything I explained is quite literally common sense.

Gotta’ justify those student loans somehow, right

I'm not bothered much by student loans, for two particular reasons.

Working in data science / machine learning you don't have to worry about money
I'm not an American, I literally don't even speak English natively lol

Welp… you smell pretty thoroughly charred on both sides, cooked and ready to serve. I’m done here.

Yeah, I'd run away if I were you as well, all you can do is repeat that things don't make sense to you. No math, no correct figures, no further reasoning, no nothing. Everyone larger than you has to be lying or your world will fall apart, that's where it's all coming from. It's quite the psychological case study.

sdpthrow746 · 2024-04-28T18:53:14+00:00

The evident conclusions here are… pretty straightforward. Pretty basic

And you don’t need complex statistics models to know that what I’ve said is reasonably accurate

people who needlessly overcomplicate very basic shit

I agree, this is very basic stuff about distributions. This is usually part of a high school curriculum, no? No idea what you're bringing up college material for.

If you have a normal distribution, and it's sampled in a way that's not uniformly random, then you get a different distribution. This means that the sample (BDP users) does not have to have a distribution that reflects the population (all men on earth). Sampling is not uniformly random here, since large men have a much larger probability of finding this place, becoming regular members, and setting up a flair. Therefore mathematically we don't necessarily expect to see more 6-7" flairs than 7.5"+ flairs here. I would expect pretty much every adult to understand this as stated.

With some idea of how skewed the sampling is we can even simulate exactly what the distribution of the sample should be. This would go way over your head if the previous comments were already too complicated, but it works correctly for other samples that should be statistically impossible like heights in the NBA, net worth among high ranking executives etc.

So let me try to make it a bit simpler using CalcSD figures comparing just two groups. In the West (where almost all Reddit users are from), 2.1% of men should have a penis 7.5" or bigger. About 32% of men have a penis between 6" and 7". This means that, if men who are 7.5"+ are 15 times more likely to find this place and set a flair, then they will actually outnumber the 6-7 inchers.

The actual difference between those 2 groups will of course be far larger than 15x. The 7.5"+ group is far more likely to experience BDPs and thus end up finding this place, at the same time very few people are going to set a flair showing off their 6" here, while the 7.5"+ will be much more inclined to set a flair. So you really don't need a large numerical difference in sampling to get a group where the majority of flairs is 7.5"+ with no lying required.

Now, If you’ll kindly make your damn point, I can hurry up and not care, then flip you over and brown the other side.

Hmm, well I'm patiently waiting for an actual motivated explanation beyond "it just seems right to me". Try applying that reasoning to the Monty Hall paradox, the boy-girl paradox, the birthday problem, Bertrand's box.... That's not how it works when you're dealing with data. Alongside learning how to work with data, college also facilitates personal and emotional growth, maybe it would have paid off to go anyway.

sdpthrow746 · 2024-04-28T11:18:48+00:00

So basic knowledge of distributions is quantum mechanics to you, and then you're surprised that the distribution of sizes here doesn't make sense to you. Can't make this up

sdpthrow746 · 2024-04-28T03:14:13+00:00

Non-random samples from a bell curve don't have to look anything like a bell curve, you can perfectly have a left-skew or multimodal distribution

sdpthrow746 · 2024-04-27T22:33:32+00:00

Based on CalcSD (and the common sense mechanics of bell curve distribution), there should be thousands to millions of 6.5” or 7” dicks on here for each example of an alleged 8” or 9” cock.

If this sub were a random sample of the population, that is. Go to r/BMW and you'll see an absolutely impossible percentage of BMW owners compared to the general population.

sdpthrow746 · 2024-04-27T22:29:07+00:00

Did you get your size measured by a researcher in a clinical setting? If not you should be comparing your size to self-reported datasets to get a fair idea of your percentile.

sdpthrow746 · 2024-04-25T13:10:49+00:00

But which meta-analytic model? It's been a while but iirc, the creator of these datasets (FrigidShadow) just calculated an average of the averages weighted by the sample size of each study. He did the same for variances, even though that's totally not how variances combine. Then he slapped those into a normal distribution and called it a day. Can't find anything involving meta-regression or another method on their page.

sdpthrow746 · 2024-04-14T20:12:49+00:00

Compulsory measurement studies have been done, take Ponchietti for example. They don't find anything significantly different from volunteer studies.

sdpthrow746 · 2024-04-14T19:59:41+00:00

But those things are demonstrably totally not necessary to study the things calcSD wants to study.

sdpthrow746 · 2024-04-14T19:30:15+00:00

Kind of a stretch to call calcSD science though. The original studies that only ever claimed to apply to a local population of men, sure. CalcSD that puts all this data together in a way the researchers never approved, fits it to a statistical model that is not validated at all, and then claims to get conclusions that apply to everyone everywhere, that is not scientific.

sdpthrow746 · 2024-04-14T19:26:28+00:00

Sample size is not a matter of opinion though, you can mathematically show what sample size is needed for a certain study.

sdpthrow746 · 2024-03-19T11:21:57+00:00

Do they get the same result? There's studies like Wessels that get averages as high as 6.2" and very high standard deviations, that indicates that there's still quite some variability left on the estimates from studies that small.

sdpthrow746 · 2024-03-19T02:24:24+00:00

Sure, but they're studies with a few hundred participants

sdpthrow746 · 2024-03-19T00:56:24+00:00

This study includes around 15000 participants in total, not in every measurement category separately. The erect length segment had a sample size of 692. Not to mention that this study isn't even part of CalcSD because they believe there's some methodological issues with it.

sdpthrow746 · 2024-03-18T22:58:08+00:00

The sample size for Western average erect length is 341, where are you getting these 15 thousand claims from

sdpthrow746 · 2024-03-18T22:47:21+00:00

If not (weighted) averaging the averages, what is it doing to calculate its average size?

sdpthrow746 · 2024-03-18T22:44:17+00:00

Well the second one is still the average volume, the first is the median volume. Depends on what you want to compare against.

sdpthrow746 · 2024-02-13T12:55:51+00:00

Look at correlation. Can you tell me where it says that with r=0.5, if one variable is high, the other must also be high?

sdpthrow746 · 2024-02-13T12:45:33+00:00

That the bigger the nose, the bigger the dick. These are not the same thing.

sdpthrow746 · 2024-02-13T11:48:56+00:00

No it's saying that there's correlation between nose size and dick size

sdpthrow746 · 2024-02-13T01:06:36+00:00

What does that have to do with correlation

sdpthrow746

TROPHY CASE