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Aella recently made an online survey about escorting and posted a chart on Twitter. It shows monthly earnings binned by BMI and clearly depicts that escorts with lower BMI making more on average than escorts with higher BMI. I would not have thought anybody would be surprised by that. The comments under the post proved me wrong.
Christ almighty, I had no idea that there are so many statistically literate whores around just waiting to tell you your survey is bad. I also wasn't aware that escorts advertise their services so openly on social media.
The number of escorts, both slim and not so slim, calling her out with little to no argument is mind blowing. The arguments they do give basically amount to sample size too low, BMI isn't real or "your survey is bad, and you should feel bad". Some of them also appear to lack reading comprehension. They point out that a sample size of 30 doesn't tell you anything meaningful. The post, however, clearly states that the sample size is about 30 per bin (which Aella points out is kind of low), making it about 150 total. Some give the argument that they themselves have high BMI but earn way more than that, and therefore the survey result must be wrong. Averages are seemingly a foreign concept to some.
A lot of them don't give much of an argument at all but question her intentions. Why would anyone be posting such dangerous information targeting the doubly marginalized group that is fat escorts? Their point seems to be that such information serves no purpose for anyone and should be kept hidden, which is ridiculous, since any woman considering escorting must have an interest in how much she can expect to earn based on her body type.
Others claim Aella is trying her hardest to stir the pot for attention. That could have been a valid point, if what she posted had been the least bit controversial. If you went out and asked 100 random people, I can't imagine that more than a few would say they believe fat escorts on average make the same as normal weight escorts. I also can't imagine any of these offended women would have any sort of problem with a chart showing that taller men make more on average than shorter men.
A few are asking what Aella's credentials are or whether the survey has been reviewed by an ethics committee, as if you need any of that to do a random google forms survey on the internet. They appear to believe that ethics committees are to protect people who might find the result offensive and not the participants of the study.
I also can't help but find a bit of irony in prostitutes trying to discredit someone based on their credentials.
Anyways, the data from the survey is available on Aella's website. I had a quick look at the correlations. It seems to be mostly what you would expect, but one thing that I don't get is that condom use shows no correlation with contracting STDs, which makes me quite suspicious of the data. It isn't correlated with education level either, but somewhat correlated with doing the job out of desperation (0.19). I would assume it would be the other way around. What is even crazier is that condom use is slightly negatively correlated (-0.11) with having a romantic partner. That seems absolutely insane to me, but maybe they use protection when they are with their partners?
Are they survey and response items up anywhere for people to see still? I ask because a lot of the data in the raw data sheet seems, frankly, weird.
For example, column "O" in "Sheet1" is the question "You typically use a condom:" and the results in the column are almost all integers. It is not clear to me where these integers are coming from, or what units they are supposed to have. Are they the number of the result item the respondent selected? Ex "1" represents someone who picked the first item, whatever that frequency was? If this is the case I am not sure running a regression using these numbers as your values will yield any sensible result. Similarly several rows in this column have an identical non-integer value of "2.293838863". No idea where this value is coming from or what it means in the context of the question.
Or take column "BT" in "Sheet1", which is the question "About how many times in a year do you get tested for STIs?" I expect answers to this question to be nice integers (you can't exactly get tested a fractional number of times) but again a bunch of columns have an identical non-integer value of "6.37414966".
Perhaps relevant to the BMI/income buckets a bunch of rows in the "BU" column ("Estimated Monthly") also have identical values of "1428.597195". Aella mentions this is a computed column but I'm having trouble figuring out how. Most of the non-identical values seem like sensible number ("900", "2700", "9900") that I can see being computed from the given figures of hourly rate (column K, all multiples of 50, no repeating weirdness) and duration (column L, values from 0.5 to 8, all multiples of 0.5, no repeating weirdness). Where the heck did the repeating decimal come from?
You can see this pattern across a bunch of columns where integer values don't really make sense as a response (column N, "What services do you offer, primarily?") and there are some bizarre identically repeating values (all with substantial decimal significant digits). It's not even like it's the same rows that have weird values for every column either. There does not seem to me any relation between which columns have these rows across columns.
I'm also interested in the procedures for generating the correlations in "Sheet3". There are listed correlations for categorical variables (like the aforementioned column N) but what procedure was used to generate them? The procedure for calculating the correlation between different kinds of variables (ex, categorical vs continuous) are different. Were the results of column N treated as categorical (how do you do a categorical calculation with the weird decimal values?) or continuous?
Nice find! Feels like this should be more prominently displayed than just in a box that appears when you hover over column A1 (at least, that's the only way I see it).
Yeah, I totally missed that. I still don't get why the 1428.597195 value is in the estimated monthly column. There shouldn't be any missing data in that column, right?
Correct, assuming it's calculated the way you mention in the other comment.
Row 13, for example, has all three of the columns used in the calculation populated but has the autofilled value.Rather, none of the three columns used in the calculation contain any auto-filled averages (based on a quick calculation of each columns average). Honestly, the fact that every field is a raw integer (so she didn't use Sheets built in functionality to compute these numbers) makes me wonder if there was some copy paste issue from elsewhere?I'm inclined to try and contact her and ask her to upload the actual raw data from the google form. Calling this raw is a bit of a stretch.
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I hadn't really looked at the data much, but you are absolutely right. Something is not right. I found what must be the survey responses here. I had assumed that the condom question was answered on a scale such as "never", "sometimes", "often", "always", but that appears to not be the case.
As far as I can see it is computed by multiplying columns
"On average, how many appointments do you have a month?"
"In general, the most common length of time you tend to get booked for is ___ hours"
"Hourly (ADJ)"
This matches the values in "Estimated Monthly" that aren't "1428.597195". I have no idea how hourly rate has been adjusted, though.
First I thought the weird non-integer values were some sort of corruption, but the correlation in sheet3 for BMI and estimated monthly matches the column with the "1428.597195" values, but when I do it with the newly computed estimated monthly values I get no correlation (-0.077). Very strange.
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