How to Study Astrology with Data Science
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Data Science is the practice of taking very large datasets – 1 million, 10 MN, 20 MN, maybe a billion different rows of facts and statistics – and applying scientific methods to gain knowledge and insights from the data.
Many people come together to ask questions of this very large dataset (a.k.a. Big Data). These questions are typically mathematical. For example:
- How many people in this dataset go to school?
- How many people in this dataset like fast cars?
- How many people in this dataset have a sun sign in Aries?
When these questions are asked repeatedly and in large volume, this is an example of Machine Learning. Machine Learning can mean many different things, but essentially it is a lot of tallies from counting different things, on repeat. In the context of Astrology, each of the rows of data represents a single unique person in the universe. The examples we gave above “go to school, fast cars, sun sign in Aries” are all different ways to count what the data says about this group of single unique people in the universe. When the machine starts to count the data in many different ways all at once, then the magic starts to happen!
While counting the data in many different ways, the machine is also calculating whether any of these things correlate to each other. Correlation is whether two different things are more likely to occur together than two other things. For example, if “I like purple” occurs more often with “I like black” than “I like purple” occurs with “I like orange”.
What does Data Science have to do with Astrology?
Many people think Astrology is like a fortune cookie. Some stereotypical “woo-woo” new agey person shows up in your inbox or magazine and says something like, “Today is likely to be heavy on the Aries energy with a chance of rain.” These days Astrology is sort of like the “energy weather” of the day or week or year.
In reality, Astrology is very complex. There are like a million things (a.k.a data) to count in Astrology, and so also like a million things we can test with Data Science, Advanced Statistics, and Machine Learning.
Astrology is one of the first sciences that human beings created. Across civilizations, ancient people counted celestial bodies and observed their behavior to understand the environment around them: when the sun rises and sets, how full the moon is and when, the relationship between the time of day and optimal times for hunting. They observed and counted the number of days between full moons, the planets they could see, how they moved across the sky, and the pictures the stars made.
The ancients used this celestial data to create the Zodiac. Although the ancient Zodiacs differed across regions and cultures, they became scientific and mathematical tools that helped people keep time and predict the future. People began to use these tools to create assumptions: if there is sun it is “day”, on the 7th moon the wheat will bloom,
The Zodiac also began to tell a personal story about an individual based on the stars they were born under and assumptions were created based on this data: people born with the moon in Capricorn have strong hands, people born with the sun in Aries have red faces, and so on. Some of these assumptions are easy to prove and some are harder.
Are all people born with the sun in Aries red in the face? No. This one is easy to disprove. But there are millions of other assumptions in Astrology we can look at with Big Data, Advanced Statistics, and Machine Learning. Which begs the question: What can we say is actually true about Astrology with statistical significance? This is where The Ratio comes in.
Our team of expert astrologers and scientists are working to uncover what we can actually know about Astrology that is scientifically true and statistically significant. And there is much to discover!
In the beginning of Astrology, most assumptions relating to the human individual were about a person’s appearance. For example, Geminis were tall, thin, and used big hand gestures.
As Astrology evolved over the centuries, it became more about personality than about someone’s appearance. Today in Western Astrology we say Geminis like to see “both sides of things” and hate making decisions.
There are hundreds of these kinds of assumptions in contemporary Astrology. But how true are they?
Using Big Data we can test these assumptions. We can ask: Are all the Geminis in this data set more likely than other signs to waver in decision making? For example, are Geminis more likely to post on social media and then go back and edit it?
This is where Advanced Statistics and Machine Learning helps us do Data Science on Astrology: we can look at the data to see what traits, behaviors, and beliefs are more likely to correlate with Gemini than with any other sign. We can ask the data anything we want to know.
Astrology has always been a science. It is a big, brave, and bold thing to consider all of human history and continue this ancient practice with modern technology.
After all, humans have grown, preserved, and practiced Astrology for thousands of years. We think it’s time to begin the next evolution.
What Happens Next?
We don’t anticipate we will find Astrology is “all true” or “all false”. Rather we anticipate we will find some assumptions in Astrology are true, some are false, some are inconclusive, and some require us to interpret something new.
The collection of all our learnings will become The Ratio’s unique offering: Astrology backed by Data Science, Statistics, and Machine Learning. Only assumptions we can prove in the data will be included.
Gazing further into the future, we dream of merging Western and Vedic astrological assumptions.
We invite you to join us on our journey to “look once more upon the music of the spheres” with the most advanced technology and mathematics humanity has so far.
We look forward to evolving Astrology once more with you.