BYE2020

The Science of Astrology

In December 2017, I set out to answer what I thought was a rather simple question: Do court cases decided under the influence of Mercury retrograde have a greater than average chance of being reversed on appeal? Little did I know that I had just fallen down the rabbit hole. 

Pursuing the answer to that question consumed my life for the next 22 months. I spent more than 1,500 hours, and many thousands of dollars on this research. I knew I was on the trail of something profoundly important, but it took almost a year before I had even an inkling of what this research was really about. 

What it’s really about is scientific proof of astrology. 

But that doesn’t mean quite what you think it means. 

Connecting Big Data to Astrological Research

What made this project possible was the discovery of Big Data. I discovered a website where I could download 40 years of Federal Court records, including all of the original case data and the appeals case data. Ultimately, I considered over 835,000 Federal Civil Appeals Court cases for this part of the study. 

But it didn’t stop there. 

I also discovered that the Department of Transportation had an online database of every flight that departed a U.S. airport since 1988, including how late each departure was. So I was able to analyze more than 172,960,000 flights. By then, I was obsessed. I needed more data. 

With some help, I was able to obtain details of 12 years of Amtrak train on time performance (over 10,000,000 trips). And then I started to wield Freedom of Information Law requests and was able to get On Time Performance data for city buses and light rail from Chicago, Dallas, Seattle, Philadelphia, and San Francisco (more than 500,000,000 individual stops in total).

I was able to obtain data on car crashes, first from the Fatality Analysis Reporting System (FARS) that tracks fatal highway crashes, and then some data on police-reported crashes in California, Iowa, Michigan, New Jersey, New York (city and state), and Texas. 

And when it came time to look at forecasts, I had the entire stock market to consider. The study looks at a total of 430 financial instruments, including 10 stock market indexes, 379 individual stocks, 21 commodities, 10 interest rates and bonds, and 10 currency exchange rates. 

At least in terms of data, this is unquestionably the most significant astrological research study in history. 

But It’s Not Really About Mercury Retrograde

When I set up the original study to look at the court case data, I knew that just considering Mercury retrograde would be a waste of time. My personal experiences were that Mercury causes the most mischief when it’s slow. Once Mercury picks up speed, even if it’s retrograde, I don’t notice issues, but the three or four days on either side of the stations are always challenging. 

I focused on the average daily motion of Mercury. I discovered that Mercury can travel up to 2°12 a day in direct motion, and up to 1°23 a day in retrograde motion. I ran an ephemeris for Mercury from 1975 to 2030, and assigned each day a category based on the average daily motion. Initially, I broke it down in 30-minute increments (M30), and later created a second series that was divided into 15-minute increments (M15). 

My initial results from the court study suggested that when Mercury is slowest, it matters if it’s decreasing in speed or increasing in speed. So I created individual categories for the direct and retrograde speeds on either side of the station. 

I discovered (much to my dismay) that Mercury retrograde doesn’t really do anything. There were no statistically significant results anywhere looking at only the speed. But when I combined the sign and speed, things got very exciting. 

For the first year of this study, I believed it was about astrology. But in December 2018, I finally realized that the study isn’t about astrology at all. 

It’s about statistics. 

Seasonality, Statistics, and the Nature of Time

This is where things start to get really complicated. First, it’s important to understand that I knew virtually nothing about statistics when I started this project. Everything I learned, I learned by making repeated, disastrous mistakes and basically misinterpreting every single result in the whole study multiple times. I don’t assume that anyone reading this knows any more about statistics than I did when I started, so I’m going to do my best to keep this very simple. 

One of the most important functions of statistics is the analyze data on a timeline. Statistics looks for patterns in the historical data and uses those patterns to forecast future results. The fancy term for this is “quantitative time series analysis and forecasting.” 

An important part of this is something called seasonality. Seasonality exists when a pattern in the data repeats in regular intervals. Statistics looks at seasons based on calendar and clock time: quarters, months, weeks, days, hours, etc. 

What I discovered is a whole new world of astrology-based seasonality. These Mercury cycles are seasons in time. But they’re nothing like any seasons we’ve seen before. This is irrergular seasonality. These seasons last for different periods of time, they don’t repeat in the same sequence, and they don’t repeat every year. And if you’re considering the M15 Sign and Speed seasons, there are 202 of them. 

In my research, I proved that these seasons exist across multiple, unrelated data sets. And I also proved that when you include this astrology-based seasonality in forecasts, it improves the accuracy of the forecasts. 

Potentially, this will do to the science of statistics what quantum theory did to the science of physics. I have literally discovered an entirely new field of scientific research. 

When you view a drop of water through the lenses of a microscope you can see microorganisms that can’t be seen with the naked eye. When you view time through the lenses of astrology, you can see patterns that can’t be seen with the naked eye. 

And that’s just the beginning!

I’ll be adding content here, including videos and articles, that will share specific aspects of the research. At the moment, you can read the abstract of the studyStatistical Astrology: The Use of Irregular Seasonality in Quantitative Time Series Analysis and Forecasting, and you can also watch a video of the World Premiere Presentation of the research

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