Renay Oshop, uses big data, AI and advanced statistics to challenge what science thinks it knows about astrology.
photo by: Skeptiko
On this episode of Skeptiko…
Renay Oshop: We decided to just grab a screenshot of the top 1000 people who have [the highest] Twitter follower numbers, people like Justin Bieber… he had the most Twitter followers, Oprah Winfrey was in there, Dalai Lama was in there. Then we looked for their charts…
Alex Tsakiris: So the chance of these celebrities having that [particular] alignment of those planets is over 90%, and then of the control group, it’s 45%… the odds of that just being chance is far less than 1 out of a hundred right?
Renay Oshop: That’s a good summary, so that was step one and then step two on that paper was to show a correlation…
Alex Tsakiris: So of your list of 86, those are spread across the top 1,000 ranking, so you might have somebody and they might be down [around 900], but the the real stunner is that any one of those 86 who happened to rank in the top 100 had a 100% correlation between that and having this certain position of the planets.
Renay Oshop: That’s absolutely right, that’s what we found.
Alex Tsakiris: Wow, that is pretty incredible.
Stay with us for Skeptiko…
Welcome to Skeptiko, where we explore controversial science and spirituality with leading researchers, thinkers and their critics. I’m your host, Alex Tsakiris, and this introduction’s going to be a little bit of a long one, because this story today is a long one, an interesting one. It’s about astrology.
It starts with me getting an email — the kind of emails I love to get from a Skeptiko listener who’s well-informed, is science orientated, and is digging for more. The email is from a guy named Jonathan and he writes…
Dear Alex, I write you as a huge fan of your show, out of all your guests it is Dr. Julie Beischel and her rigorous methodology that has impressed me the most. She clearly has a love of science and uses the scientific method to discover knowledge once thought undiscoverable.
In that vein, I wanted to introduce you to the work of Renay Oshop, she’s using her genius level mind and mathematical skills to investigate astrology and getting results like Dr. Beishel’s.
Now Jonathan goes on, but you get the gist of the email. It Catches my attention. I love Julie’s work, exactly as he said, using scientific methods to unmask bullshit scientific paradigms, he doesn’t say that, I do, and give us a better sense of what’s really going on in these kind of fringe areas that we think may be somewhat true, but we can’t really put our hands on.
Astrology? Hey great, [it] fits into that category. We all know it’s bullshit, right? Well, we all kind of think it’s bullshit, but we kind of think maybe there’s something to it. We know the Ancient Chinese were into Astrology, and we have Vedic astrology from India, and then of course we have Ancient Egypt and Babylon, and a lot of history that somehow rolls into the astrology that we see today and gives us this sense that — while this daily reading stuff that we read might not be true — I think a lot of us have a sense that, maybe there’s something there that all these great traditions, for thousands of years, knew about.
Now, of course, what also makes this so interesting to me is that when you turn to science and say, “Hey, from an observational standpoint, we have a question, is there anything going on here?” What you get is classic scientism. Opinionated dogma. I wouldn’t believe it, even if it was true.
As an example, after doing this whole show, I was listening to Joe Rogan, who of course everybody knows; he does this excellent podcast, even though he sometimes can’t get past this kind of inbred skepticism that he has, but anyways, he’s got Neil deGrasse Tyson on the show — one of the most famous atheist scientists of our time, who everyone thinks is so smart. I don’t get it, I don’t think the guy is that smart. I mean, I’ve interviewed dozens and dozens of people on Skeptiko that I tell you, just from intellectual horsepower, able to handle issues, seem a hell of a lot smarter than this guy.
But hey, everyone’s romanced with Neil deGrasse Tyson, he’s a great presenter. So anyways, they were talking about astrology, here’s what they say…
Then you go to the astrologer’s tables and they say, oh this is the rain sign or this is a drought sign, and then you take the names of things and those names are what they interpret. Based on where the moon is, the sun is, where the planets are, and all, whatever the angle configurations there are and each angle has a certain latitude over which they’ll count it as a hit, rather than as a miss. So this give extraordinary capacity of the astrologer to tell you what’s going on in your life.
Ah, so it’s bullshit?
So, classic Neil deGrasse Tyson, he’s mixing in some stuff that’s probably true, factual, with just some bullshit crap that he’s never investigated. Here to me is the scientific question about astrology: Is there a correlation between the positioning of these planets and events that are happening down here in the physical world? That’s it. Because look, when science enters into a fringe area it has to work from the ground up, right? It has to work from observation, to correlation, to causation. I mean, it would be great if you could start with causation and say, “Hey, we found these two things cause each other, now let’s go out in the real world and find out all that stuff that happens.” But that’s not usually the case.
Take for example, you know, our buddy Rupert Sheldrake, right? Cambridge biologist, does all this fringe stuff —dogs that know when their owners are coming home — but he also does this great thing with the staring thing, right? So this is that where we have this sense that we’re being stared at, and he wanted to look at that.
So you start with the observation. The observation here, in that case, on the staring phenomenon, is that we have overwhelming anecdotal data. If you go to people who do professional surveillance, they say, “If you’re following somebody, don’t stare them in the back of the head, they’re liable to turn around.” If you go to spies, if you go to undercover detectives, I mean it’s part of their training, they say, “Don’t stare at the back of somebody’s head.”
So this, for a trained biologist like Sheldrake, [who] says, “Hey, this seems to be occurring in the natural world, let’s go, run a test, and see if we find a correlation.” So the correlation would be, if I stare at the back of your head for this given time, under these controlled conditions, do you turn around? That’s the correlation. And, when you find that correlation, like Sheldrake did, it should change people’s minds. People should go, “Wow, that’s important, that’s science. Now let’s look for a causation, let’s look for a physics kind of explanation for what might be going on.” But you don’t deny the correlation, because the correlation is this really important part of this process.
So, similarly, if you will now, let me switch back over to astrology. So, for astrology, the scientific question is, is there a correlation between the planets, sun, stars — whatever — being in this particular position, and the events happening in the physical world? If there is that correlation, then we would have to investigate further and figure out what the causation is, but we’d be down the track of saying that astrology has some realness to it.
So, you know, I was kind of getting on Neil deGrasse Tyson earlier, because he seems to miss that point. This question has been asked for a long time, and the results of it have been mixed. I mean, sometimes people have found that correlation, sometimes they haven’t, you don’t get any sense of that from what he says. That’s because, what he’s really doing is just promoting a particular world view, this status quo, keep everything going the way it is, kind of world view, and it’s disguised. People like Joe Rogan, who is a super smart guy, […] just don’t catch onto that part of the game, and it just kind of slips past.
But, it’s not going to slip past us today on Skeptiko, hopefully. In fact, my story, right? So I contact Jonathan, and Renay’s work immediately has my interest, because I investigate a little bit further, I look [her] up, and Renay is published in the Journal for Scientific Exploration, which I know is a very good journal. I’ve had editors of the journal on this show, I’ve had people who have been published in the journal on this show, and I know, from talking to them, that it’s not only an excellent journal, it’s brave enough to tackle these controversial areas of science, but it’s also a hard journal to get into. In fact, referring back to Dr. Julie Beichel, she’s told me that she’s published in several academic journals, and that the review process for JSE, Journal for Scientific Exploration, was by far the hardest review process that she went through.
So, it’s a real deal, and when I saw that she had published there, my interest was peaked and I really wanted to go forward with the interview. But I still had, in the back of my mind, these questions, concerns about astrology being mostly bullshit.
So, I set up the interview with Renay, and at the same time I said, “Why don’t we do a reading?” Because, let’s be clear, Renay isn’t just an astrology researcher, she’s also a practicing astrologer. So, she provides that service, people pay her for that service. I paid her for that service, with the understanding that I would use it in the show as part of this exploration of astrology and astrology research.
So, we got everything set up, and then we went ahead and did the reading, and the reading was not very good. Not very good at all. And some of the things that really concerned me about the reading was, not only was it not accurate, but Renay seemed really uncomfortable with the fact that the reading wasn’t kind of working out. I wasn’t. I was like, “Hey, I get that these things aren’t perfect and that they don’t always work,” and that there was this question about the time of my birth and whether I had that right, which I didn’t, and I later confirmed by getting a copy of my birth certificate. But the whole reading was making me question the idea that you can really give somebody the time and place of your birth, and they can start telling you all these precise things about your life and what’s going to happen in the next 90 days or couple of years or any of that stuff.
So, I was in this space, I wasn’t put off by Renay’s reading and I was ready to move on and do the next interview we had scheduled, to really talk about her research. But the email exchange we had after that reading changed everything.
So, Renay freaked out. She goes, “Oh my god, that was such a terrible reading. Please don’t publish it. I don’t want to do any more interviews. I should have never done this. I’m out of here.”
So I was surprised, I was really surprised. Because again, during the reading I said, “Hey, this is no big deal, I’ve had medium readings from really good mediums that didn’t go well and yet I still believe there’s after death communication, and I believe there’s people who can facilitate that. So this doesn’t matter all that much to me, let’s talk about the research.” But Renay was in freak-out mode and the more I talked to her through email, the more pissed off I was getting. Pissed off because, if you’ve got the goods, if you’ve done the research, you ought to be able to suffer the slings and arrows that come with being on cutting edge science.
Now, as I say that, there’s another side of me that wants to highlight how fricking difficult this crazy biological-robot, scientific-materialism stupidity makes it for people to endure, to persevere, to push their research forward when it goes against this kind of dogma. And I think, I suspect, that’s what was going on with Renay.
But still, I don’t cut her any slack. Hey, if we’re going to push this edge, we’ve got to expect the pushback and we’ve got to push through it.
So, I went back to Jonathan, the guy who originally turned me onto Renay, and we had a long talk and I told him exactly what happened and I told him the same thing I told Renay, “Hey, I’m going ahead with the show, and if you want me to do the show with just your crappy reading, then I’ll do that. If you want to come out and explain yourself, and stand up for your research, then maybe we’ll have a different show.”
Now, fortunately Renay came around, and I think we had a darn good interview about, what I think is some incredibly important research concerning astrology. There is no doubt she’s super smart, super capable — she’s using AI big data, very sophisticated statistical techniques, very solid science to bring forward a new picture about what’s going on here, one that you’ll never hear Neil deGrasse Tyson talk about, because he’s a boob.
Anyways, if you really just want to, as Jonathan said in that opening email, discover a knowledge once thought undiscoverable, here you go.
One more thing, if you’re listening to this interview, it starts, again in kind of an unconventional way because, for the first time in my conversation with Renay, getting on Renay for backing out of this initial interview, and I think I pushed her pretty hard, but to her credit she withstood it, and then we eventually got into the interview that we both wanted to have.
Alex Tsakiris: You published in JSE. You must have taken a lot of criticism, because that’s part of the process, but maybe you didn’t. Maybe you slid the whole thing past them. Maybe they never asked really hard questions; they were just bamboozled by the data. I don’t know, but I tell you what, I didn’t have those questions going in, and like I say, I was totally on board, because I’ve interviewed several people that have published in the JSE, and they’ve always told me, “Hey, it’s really hard, you know, the reviewers are really tough,” and this and that. So again, I had that assumption, but no Renay, I don’t have that same assumption about your work, so now that’s where I’m at.
Anyone that listens to the interview is going to know that the reading wasn’t good, but who cares; it’s just one individual reading.
What I’m trying to figure out…is this research worth anything is the second part of that, and when the researcher can’t stand behind [her] research, well then, you know, that just raises a lot of red flags.
What I express to you was my bias based on my experience was, everything thinks they’re 95%. All the psychics think they’re 95%, all the mediums think they’re 95% and you’re telling me you think you’re 95%. You know what, you’re not 95% and no one’s 95%, but that doesn’t take away from the fact that it might be real.
So here’s the question, the real question in my mind, through the whole thing is [that] I have no doubt that astrology works, but does it work in the same way that Tarot works? Does it work in the same way that reading coffee grinds work, in that the individual person is connecting to extended consciousness realms, which we don’t really understand what they are, but we’ll just put that name on it — is that what’s happening? Is astrology a means for the person who’s doing the individual reading to connect with this extended consciousness and bring forth information.. is that’s what’s happening? Or is there some real physical — materialistic really — connection between the layout of the these planets and these stars and what’s going on?
I don’t want to misrepresent the show one way or another, I’m not an advocate for astrology, but I’m not here to debunk astrology and your research in ways that it shouldn’t be, but tell me why someone’s who skeptical of your research should have confidence in it.
So let me interject something here. So we’re having this conversation Renay and I’m telling her some of the problems I had with the way she handled things and I’m very, very skeptical of her research, but I’m trying to figure out whether we should go ahead with the show, and I’m being pretty hard on her, but then at some point, we switch over and we start talking about her research. So let me just give you — we talk about it at length, in this interview — what the research is, but it might be helpful her to kind of understand, big picture, what we’re talking about.
Two pieces of research that Renay did that are really fascinating. One is [that] she looked at Twitter followers. She took this idea that there is this planetary alignment that would suggest that some people are more likely to be famous, followed, celebrity types than other people, right? So that’s something you could test — see if there’s a correlation — and that’s what she did.
The other thing that she did, which is really interesting, [is that] she said there’s this Mercury Retrograde thing that’s been around for a long time; people have talked about that, “Hey, people kind of go nuts and can’t do mental functioning the way that they normally do when this thing happens,” and she did some research on that, trying to correlate it with common spelling errors in this huge database of Amazon comments.
Again, a very clever bit of research that you’ll hear a lot about, but I wanted you to at least have big picture view of these two pieces of research that we talk about as this goes on.
Okay, back to the internet, here goes.
Renay Oshop: But again, I want people to tear it apart with a fine-tooth comb; that is what happened at JSE. I did rewrite it three times, and it was an awesome experience. I learned a lot of from it, and I appreciate that JSE all the more for that experience.
Alex Tsakiris: Here would be some potential criticisms that you are likely to hear. So, I spoke with one person that I feel very confident in their research and I feel very confident in the process that they’ve gone through with JSE again, the Journal for Scientific Exploration, that I keep saying I have this high regard for, and he pointed out a couple of things. He said, “Number one, there’[re] no huge red flags in the research as it stands”, he goes, “if you want to talk to the JSE editors, number one they’re not going to talk to you, they’ve done their thing and they’re not going to come and kind of answer those kinds of questions. But number two, if they did answer those questions what they’d say is, ‘Based on the data that we have for her and her representation of it, yes, that’s what we analyze. We can’t analyze whether or not she really did it exactly the way that she did it,’ and that’s where replication would come in.”
So, do you agree with that, and number two, what about this issue of replication, what about someone who says, “Okay, that’s all well and good what she’s written there, but without replication, we don’t really know if it’s real.
Renay Oshop: I would worship the feet of anyone who would want to take that project on. I would, seriously. I would love it if it were attempted. Replication, I hope, would come back the same as what I put out there, but it may not. That’s the point of replication. I want replication, I would love a replication; please replicate me, anyone out there listening.
Alex Tsakiris: How would someone go about replicating your work?
Renay Oshop: I would send them methods and materials; my approach is all laid out there. I have available all of my data in the form of screenshots, because I took the data from Twitter, at a particular snapshot and time, so they could totally just follow the steps, A through to Z, and the methods and materials that Twitter pay for, for example. I release the datasets and I release the methods and materials.
Alex Tsakiris: Okay, this isn’t a red flag per se; the other thing that my friend said is, “You know one thing that kind of just doesn’t totally sit right is, I don’t see any missteps here, I see just kind of a lock step. You know, oh, this is just what we set out to do and we did it and it all came out great, and..”, he said, “in my experience research never works that way.” What do you respond to that?
Renay Oshop: Are talking particularly about the Twitter paper or about…?
Alex Tsakiris: I suppose, because that’s in JSE, but I’d also like to talk more broadly about the Amazon misspelling one, because that’s interesting as well.
Renay Oshop: Yeah, two totally different diversion experiences. With Twitter and the JSE, that was remarkably lock step. It was where we were studying in class a particular ancient rule in astrology, and my teacher looked at me and said, “Hey we should test this with Twitter, can you do that?” and I was like, “Yeah.” So we did it and it was fairly lock step.
Now the Mercury Retrograde, as you can see and the material I’ve put on my website regarding it, and it has not been published yet; it has only been released in steps.
Alex Tsakiris: When you say Mercury Retrograde, are you talking about the Amazon…?
Renay Oshop: Yeah.
Alex Tsakiris: So briefly summarize what that experiment is and then please continue.
Renay Oshop: Sure. Fundamental question — hey, if there’s thing called Mercury Retrograde, we should be able to see it and things like increased tech support calls during the Mercury Retrograde, because people are having more problems, more mistakes, more misunderstandings, things associated with Mercury Retrograde. Well how do we measure such things without access to, for example, Verizon’s tech support call records? So how can we get public data on mistakes, what does that even mean? And that I happened, just during that time, to come across Stanford’s public repository of big datasets, a fascinating place to go and explore and I think it’s just called that, you can just Google that, Stanford repository big data or something like that. Anyway, they had all of the Amazon reviews from the inception of the review system in 1996 to mid-2014, that’s what 20 years… no sorry, 18 years. And so that’s a lot of data in contemporary terms.
So, what’s in there in terms of mistakes? Now, I would say, just on the face of it, there’s no record in the dataset, for example, of fixing misspellings. What we do see is a dampening, if you go into the data, of a downward [trend in] spelling mistake rates. That might be consistent with better spelling mistake catchers, you know, the software that catches your spelling mistakes.
Anyway, so you can see, I went through tons, maybe 20 iterations of that…
Alex Tsakiris: Renay, let me interject, because you were kind of the line of kind of explaining it at a high level, and then you kind of got sidetracked into […] that’s an interesting little aspect of it. So, but back to the big picture story.
Renay Oshop: Right.
Alex Tsakiris: You get this big dataset and your idea is, “Here is actually a log of mistakes that is measurable if I can somehow do this massive spellcheck on that and see if there’s more spelling errors on these certain dates and then if I can go ahead and not only do that looking back in kind of a datamining way, that people don’t like, but then if I can also predict that going forward, in saying, okay I’ve looked at this much of the data, and yeah that pattern seems to exist. Now without looking forward, let me predict what days are going to be more prone to spelling errors and let me see if that plays out.” Am I getting this right?
Renay Oshop: Yeah, I think that’s well said. That’s right, and I went through tons of mistakes on that one. Maybe because I was doing it on my own, and I wasn’t coming from any great astrological principle from a thousand years ago. I just was going into the data and saying, “Show me data; is there a periodic regular cyclic increase during Mercury Retrograde?” And using kind of classical Fourier transform, I found out, “Oh my gosh, there is, there is this regular periodic increase during Mercury Retrograde, up to 17%. Not always 17% but there is this regular periodicity.
Then I used a linear regression model to find the exact coefficients of when is it 17% per word increase in misspelling rate during Mercury Retrograde, and when is there still a Mercury Retrograde increase but maybe at 5% per word likely per increase. And using the linear regression model with the AI, I found a model that works really well is one that employs all of the planets’ retrogressions, and there’s a beautiful interaction there, Mercury retrograde just being one of them, but I believe when those retrogressions in Uranus, Neptune or Pluto and also retrogression in Mercury — that’s when it’s at its highest. But when there’s only one of those, it’s less than that.
Alex Tsakiris: How do you get at the old causation versus correlation thing? So the big complaint that everyone has, immediately when they look at astrology, is that you’re data-mining, right? So every year, one of these skeptical organizations presents this, “Ha, ha, here’s the zodiac sign that is the worst driver, right? And one year it’s Capricorn, and the next year it’s Sagittarius.” And what they’re just doing is taking the huge database of claims that are made against their insurance for accidents and they’re data-mining, looking through that and saying, “Which one fell into this group,” and they’re reporting that, as if that means anything and then they’re coming back and saying, “See this is what people do. They just data-mine, and then they report it as there’s some kind of causation rather than […] just a correlation,” which there always is in the data.
Renay Oshop: Yeah, yeah.
Alex Tsakiris: You totally get what I’m saying, but I just want to lay that out there for other people to understand. How do you respond to someone who says, “How do we know you’re not just doing the same thing?”
Renay Oshop: Yeah, we might be talking about something that is happening at the same time as Mercury Retrograde. Each year, for 18 years…
Alex Tsakiris: But hold on, that’s not really my point, I mean, I’m giving you a lob question there, and the answer is, because that’s what my fucking research shows. [That} is why you did all this fancy statistical analysis, is because you kept running it over and over and over again with different dates over time and it wouldn’t repeat. If the skeptics ran that, and you ran it for 20 years, and every year the same astrological sign came up saying yes, Sagittarius – worst drivers. Sagittarius – worst drivers. Well then they would have something, but what they’re making a joke of is, one year it’s Sagittarius and the next year it’s Capricorn and the next year it’s Gemini; well then that shows that there really is no pattern and there’s no meaning to it.
Renay Oshop: Yeah right, that right, that this is something that’s sustained. By definition I was looking for something that was sustained through the entirety of 18 years, and that happened during the retrograde, and I just want to point out that you brought up causation, and I’m not speaking to causation in my research at this point. I would love to get there, but at this point, we are talking about the first step, causation studies, as I understand it, and that is correlation.
Alex Tsakiris: Right and I think that term, we should add that that term is just misused and misunderstood by people, right? It’s become such a trite axiom that people lose sight of it. It’s exactly what you said, you know, a really good correlation; it’s carefully done and is definitely a pointer towards causation.
So what [that] axiom was supposed to point out is that a poor correlation — like I was just saying about the fact that you can data mine out with one year of data, which astrological sign is the worst driver — well that’s really a very poor correlation, right? So maybe you can expand on that.
Renay Oshop: Yeah, there’s going to be some sign that is the worst driver for a year or a month or a day and even for a decade; there’s going to be someone at the peak — at the top of that histogram — of sun signs and driving accidents. Yeah, this whole idea of causation is huge, I mean, even in medicine it’s a huge thing to show that something causes something else. But yeah, the first step is to show a correlation, and we showed that in the Twitter paper pretty well. It’s subsequently in the Mercury Retrograde; we showed it too and then also I showed an AI prediction engine [that’s really accurate] can be brought from it using standard measures of AI.
Alex Tsakiris: One thing we might want to do, just for its sake… we kind of glossed over the Twitter thing. Maybe you just want to explain it at a high level, what the Twitter experiment set out to do.
Renay Oshop: Sure, yeah, thanks. There’s this sutra in Sanskrit, from a book from a thousand years ago, well understood to be a thousand-year-old text, that says that when these particular planets are in squares to each other, at 90 degrees to each, that the person is more likely to be famous, that you can interpret the chart as being that of a famous person.
Alex Tsakiris: Okay so again, breaking it down to kind of a six year old kind of thing, your astrological chart is based on the position of the planets and the stars when you take your first breath, there’s this Vedic astrology that’s been around for a long time and it has all these axioms and ideas about what to do, and you say, one interpretation you say, is when these two things are this particular position, that means the person’s going to be famous, right? So go ahead, continue with the story.
Renay Oshop: Yeah thanks, more exactly in the exact words of the Sanskrit, that the person has a lot of followers, followers. And so, we were just chewing on that idea, followers, and we’re like, well what does it mean nowadays to have a lot of followers? Twitter! Twitter is a numerically assessable, accessible way to find out how many followers a person has, and it’s different from fame exactly. Like Leonardo DiCaprio has a lot of fame but not a lot of followers, why is that? Why do some people who are not really anything else than a Twitter celebrity have a lot of followers but not a lot of fame?
So it’s an interesting thing and you can tell that Leonardo DiCaprio has tried to, if I recall correctly. He does not have this signature — this astrological signature — for high followers, but he does have it for fame.
Alex Tsakiris: But you’ve got to realize there, that’s kind of problematic, because what a lot of people would suggest is that, one social media platform does not really… is not indicative of the number of followers. I would think that Leonardo DiCaprio has a lot, a lot of followers in the general sense.
Renay Oshop: Right.
Alex Tsakiris: So I think that, actually, doesn’t really fit with your research, because I think your research methodology is good, but I don’t think it fits with that part. So tell folks what you did in terms of defining your followers’ group versus your non-followers’ group and then how you did your analysis.
Renay Oshop: Yeah thanks. That was a fascinating process where we decided to just, in the moment and time, grab a screenshot of the top 1000 people who have Twitter follower numbers. People like Justin Bieber had the most Twitter followers, Oprah Winfrey was in there, Dalai Lama was in there and really all of them and we chose 1000 because that was the only number available, was the top 1000. So we screenshot that in a moment in time and then fed in that data, into a spreadsheet and then looked for the charts, went online and looked for charts of the Dalai Lama, Oprah Winfrey, [and] Justin Bieber.
Alex Tsakiris: So I don’t know… some of them… were you able to get more information, like birth time and birth place, and did you factor that in when you could,and when you didn’t did you just leave it out? I mean, how did you do that?
Renay Oshop: Yeah, exactly. So CNN for example has a high number of Twitter followers, but we couldn’t… there’s no birth chart for that. So all the businesses were tossed out, all the people we could not find accurate birth times for, we tossed out. Now how do we know it’s accurate? There’[re] actually astrological research sites that have reputations behind them, such as Astro-Databank. So we used Astro-Databank a lot and they’re very good at recording how they know the birth information. So we only used those Twitter accounts whose owners we had very good astronomical birth data for.
Alex Tsakiris: Do you have any reason to believe that that would have skewed the data in one way or another?
Renay Oshop: Yeah, for example there’s a lot of Saudi Arabian Princes or something, royalty who were in that top 1000, for whom we do not have good birth data or any birth data. So they had to be tossed out. So absolutely there’s geographic skewing, there’s even a time skewing. Like for instance, there’s only… so these were mostly American celebrities or some European celebrities for whom we could get the birth data.
Now, check this out: the way we got a comparison group, to compare whether this incidence of this ancient thousand year old idea, what should be seen in a chart to show a lot followers, to show whether there’s a high incidence of this combination in the celebrity group, only 86, how do we show that? Well we developed a Monte Carlo bootstrap comparison group.
Jack Efron, not Jack Efron, another Efron, from 1979 and his Stanford PhD, developed this really cool system where you can build comparison groups, you can build a comparison group from something called a Monte Carlo Bootstrap system. Where it’s okay that these are mostly European and American celebrities that were not including the Arabic group for example. It’s not bad because the comparison group is that same distribution of places, times.
Alex Tsakiris: So if I understand this correctly, the only way you can really get the astrological data that you need, to test out this sutra and this positioning of the planets is, you have to go to this website, what was the name of the website again?
Renay Oshop: Astro-Databank.
Alex Tsakiris: Which that would be reliable, in terms of getting…
So, anyways, you take your thousand off of Twitter, you pair it down in the way that you did and you wind up with 86 and you say, “Okay, we have these 86, now we want to compare that with…” probably not the correct term, but basically your control group. And then you say, “Okay, so since Astro-Databank is where we’re getting the data, we want to get the same data from that, how do we start selecting people out and not bias our selection where we just take, handpicking out ones that’ll kind of give us the result we have.” And then you say you looked at this guy who did this Stanford PhD and he said, “Yeah, there’s a way to do it using this Monte Carlo, this randomization kind of thing, where you can kind of get a good data set for your control group. So, now you do that and you have your… So how many do you wind up with in your control group and was I right that you have 86 and then what do you do from there?
Renay Oshop: Yeah and the control group, I believe is 5460 and you can find that exact number in the paper, and what we did was just generate these theoretical charts, which were constructed from randomizations, as you say, of the birth times, places, and dates of the celebrity group. So, we mixed them all up, constructed these 5400 or so comparison group charts, and these are sort of theoretical people that we can compare the celebrities to and the point there is that we can say, “Hey, there’s not a skewing, because the celebrity group tend to come from the LA area, the Los Angeles area; maybe there’s something special about the Los Angeles area? Well that’s in the comparison group, maybe there’s something special in the planets from 1964. Well, hey, that would be in the constructed comparison group as well.”
So this is a very nice technique, this bootstrap technique, to reduce all of those concerns that there’s something anomalous in 1964 or in Los Angeles or at 8 am or whatever kind of special qualities are in that small celebrity group, we can recreate those in the comparison group. So I thought it was a really appropriate and helpful approach to constructing that comparison group.
Alex Tsakiris: That’s excellent, and I think people would be very interested, Skeptiko listeners especially would be very interested in those kind of little nitty gritty details. So hence, that’s where you get this bootstrap thing.
Renay Oshop: Yeah.
Alex Tsakiris: So you can throw this dataset at it and say, “Give me a random dataset that kind of controls for these variables that might be skewed in my dataset that I want to look at and make sure that it’s equally representative of the larger group,” and it does that, very cool, and then so what are the results that you get out of that?
Renay Oshop: Sure, well we look for incidence of this astrological arrangement from a thousand years ago. Is it higher in the celebrities, the Twitter celebrities, than this huge general populous?
Alex Tsakiris: What was the astronomical relationship again, in a way that people would kind of understand it?
Renay Oshop: Sure, it is that the planet with the highest degree, like you pull up an astrology chart, which is really a birthed astronomy chart, and you look at the degrees, there’s going to little degrees next to each of the planets that describes how many degrees in 30 degrees, that planet has passed through to get into that sign, really, that constellation.
So, even an astronomer will say that, say, the moon is at 20 degrees Pisces right now, and right enough, it’s just an astronomical observation, how many degrees a planet is and a constellation. So the planet with the highest number of degrees, and the planet with the fifth highest number of degrees, should be at 90 degrees to each other.
Alex Tsakiris: That’s what the sutra predicts?
Renay Oshop: Yeah.
Alex Tsakiris: And as you just explained, that is a very measurable fact. There really isn’t going to be, like you said… you could [take] an astronomer and say, “Go up on your telescope,” and without that person believing in astrology, they could tell you whether or not that relationship between those two planets and their movement exists or doesn’t exist right?
Renay Oshop: Absolutely, completely calculable, completely hands off — no interpretation in any of the Twitter study, none. Just applying that sutra, looking for that sutra, and we found, absolutely, its incidence, I believe, is 76 out of 86 in the celebrity group and in the huge comparison group, 5400 charts, the mean was in the 40s, like 46 or something like that, 45, 44, something like that and more of the standard deviation was 7 or something. And the normal curve that is generated from that standard deviation and that means you find that the P-value of getting the celebrity chart incidence is like .001 or something. The chance of getting the celebrity incidence, given the distribution as found in the general population model of the comparison group, is very low.
So that was step one, to show that there is indeed a higher incidence, that we can say with statistical confidence, that there’s a higher incidence in the celebrity group of this ancient signature than in the general population.
Alex Tsakiris: So the chance of the celebrities having that alignment of those planets is over 90%, over 90% of them are in that range?
Renay Oshop: Yeah.
Alex Tsakiris: And then of the control group or just… not control group but the random group, it’s 45%?
Renay Oshop: Yeah.
Alex Tsakiris: And then you ran all these trials and when you run that through statistical analysis, the odds of that just being chance that the normal hypothesis, as you say, it just happened that way is far less than 1 out of 100 right?
Renay Oshop: Yeah, that’s a good summary. So that was step one and then step two in that paper was to show a correlation. So it’s one thing to show a high incidence, that’s actually kind of neat in itself, but it’s not yet a correlation, where what we would want to see in step two is that, as the follower numbers, for a Twitter account increases, the likelihood of having this incidence increases too. So there’s a positive correlation, that as follower numbers increase, the likelihood of the holder of that Twitter account having this astronomical configuration at birth, increases as well.
Alex Tsakiris: Why is that important?
Renay Oshop: Well, we talked earlier about the Mercury Retrograde study and how important it is to show correlation as a first step for causation studies, or just [that] it’s important to show correlation. That’s even out there in general science, that’s the first thing people do, is show a correlation.
Alex Tsakiris: I get that, and we can take this off if it’s distracting, but I kind of don’t get… but that part of it, I mean, the correlation you showed in that first part, in terms of someone rising in the ranks, I mean, they can rise as much as they want, their chart is either going to be there or not be there. So whether or not they rise to a level to come onto your radar doesn’t seem to be significant in what you’re measuring in terms of the correlation.
So, there’s a lot of people out there, like you said, there’s 45% of people in your control group [who] have that; they might be rising stars on Twitter in the future, you know, who knows?
Renay Oshop: Ah, but isn’t that fascinating, they might not be though, and the reason why might be because of their chart. The highest, that very highest tail, as it’s called, of the correlation, is people like Oprah Winfrey, people Justin Bieber, people at the very ‘tippety toppest’ of the pyramid there, how many followers you have on your Twitter account, in that top tail of the correlation, they all have this ancient signature.
Alex Tsakiris: So, if I understand correctly then, I misunderstood and I apologize, what I hear you saying now is that you kind of reanalyzed your 86 celebrities and you said, “Okay, now is there a correlation in terms of their total number of followers,” and again you’re saying the high tip of the followers… are they more even strongly correlated? I didn’t think that would be that significant, since you’re already above 90%, I don’t know how far you could go. But you’re saying, yeah, even the top ones, it’s 100% and then there is a correlation where it tails down on the number of followers, right? IS that what you’re saying?
Renay Oshop: That’s exactly right, yes. And that was step two, and important in its own right to not just show, okay a high incidence in the general celebrity group, yay, that’s pretty cool, but let’s go further as follower numbers go up, so do does this incidence. So that people at the bottom of the top 1000 Twitter followers, only have this incidence 56% of the time.
Now, you go up into the top 500 followers, Twitter followers, they have it at 70%. You go to the very top 100 people with the highest Twitter followers, they have it 100% of the time.
Alex Tsakiris: So of your list of 86, again that started with a thousand and you paired it down to 86 because some of the people being followed are CNN or Infowars or something like that, that you can’t even kind of… there’s no person associated, there’s astrological data associated with it. So then you pair that down and you wind up with 86 and then of those 86 though, those are spread across… that’s still spread across that thousand ranking. So you might have somebody…
Renay Oshop: Yeah.
Alex Tsakiris: …even though it’s 86 they might be down in the thousand range, like you just said. And then the real stunner what you said is, any one of that 86, who happen to rank in the top 100, 100% correlation between that and having this certain position of the planet kind of thing.
Renay Oshop: That’s absolutely right.
Alex Tsakiris: Well, that is pretty incredible.
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