Why Study Probability?
Class is in session
There is that which is, and that which we can know about what is. Both feed the other. Probability belongs to the second subject.
If you want to know what we can know, how certain or uncertain we can be, then you must study probability. A subset of probability is logic, and so if you study probability you study logic, too. Logic is probability when there is certainty. When there is uncertainty, which is in most things, you must understand probability.
To be certain is to know the cause of a thing or proposition. Another word for cause is explanation. You must be able to explain why a thing is so or not so to reach certainty. If you cannot, then you are left with uncertainty, and must have a language to express that uncertainty.
Our goal is always to reach explanations of things. We often cannot reach it. Sometimes causes are hidden. In order to understand cause, we need to understand what is. If what we want to know is the world, then we must have a philosophy of Nature. Nature is a subset of Reality, and so to fully grasp cause we also need a philosophy of Reality itself.
Sometimes we can make all of this quite formal, which in the language of logic and probability is rigor and mathematics. But we cannot always come to formality, and so mathematics is only part of probability. And not the most important part. Though it is still crucial, and so much so that many make the understandable mistake of supposing the mathematics is probability and thus is Nature. When this error occurs we reach the dreaded Deadly Sin of Reification, the Eighth Deadly Sin, and the most common in Science.
Science is, of course, the search for explanation in Nature. But since Nature is not all there is to Reality, Science is not the answer to all things. In both Nature and all Reality, probability is never proscriptive. Probability does not tell you what to do. Therefore Science cannot tell you what to do. It can only tell explanations, and of their uncertainty.
The organized practice of applying probability to Nature is called statistics. The organized practice of forming mathematical descriptions of parts of Nature is called modeling.
In the correct and proper hunger for explanation and certainty, many shortcuts have been developed, especially in Science and statistics. Formulas—rituals, really—have been given which are said to guarantee discovery of cause. They are false. Their use has led to vast and persistent error. Cause is claimed where there is only uncertainty. Because our culture is steeped in scientism, the Fallacy which insists the answers to all questions must be and are scientific, these rituals have had devastating consequence.
The worst thing is that most are unaware of this. Scientists pick off small subsets of Nature and study them. Their interest is in the subsets, and so they devote little time to thinking about the tools they use which promise them causal knowledge. Besides, everybody is using them, and all the best sources swear the tools work.
Over-certainty is more pronounced the more complex cause is, and vice versa. Man being the most complex of all things in Nature (which is not all Reality), those subjects centered around man produce the most numerous mistakes. There are far fewer mistakes and much less over-certainty in systems which are not as complex, say, electronics. The toys we designed for ourselves work well, or well enough, because cause is easier to come by there.
The Class Uncertainty is freely available to all (whatever is needed is provided; there are no texts to buy), and supported by generous patrons and readers for your benefit. The homepage for it is here.
It is designed with as minimal math as we can get away with, and still allow us to grasp the subject. This is partly because math frightens many, and mostly because math is not the essential thing about probability. It is only a tool. And when it is necessary, my hope is that the lessons can still be understood, even when the mechanics (math) of certain things will evade some pupils. Still, math will never not be useful, so it pays to learn what you can of it.
I know of no other Class like this anywhere; assuredly it is at no university. Given our culture, it likely won’t be, either (your host has been deemed “controversial”). But my hope is that in the future others will take it up and make the material broadly available and expanded. For as much information as I can give you, there is still much to do.
The Class list is itself intimidating. There are already over 70 lectures (all are on video too), and many more to come. But not all people will need all of it. So here is the rough breakdown of areas. There is much overlap. You do not necessarily have to begin at the beginning, especially if you are anxious to get to material you need for your own work.
Truth, Induction and Knowledge: Classes 1–5.
Proof Probability Can Be Math & What Kind: Classes 6–9.
Simple & Perplexing Probability Examples: Classes 10–16.
What Random and Chance Are & What Probability Is Not: Classes 17–29
Basic & Common Probability Mistakes: Classes 30–34
Simulations & Information Complexity: Classes 35–39
Cause: Classes 40–46
Models: Classes 47–57
Hypothesis Testing, P-values & Other Enormous Errors: Classes 58–65
Uncertainty & Decision Introduction: Class 66 (much more to come here)
Regression, The Most Ubiquitous Model: Classes 67–72
That brings us up to date. I will add to this list when future Classes are posted. Still to come are treatments of more complex models, especially the many excesses of time series, physics models, coincidence, and a full treatment of decision making. I’m guessing at least 30 more.
Perhaps more if people have more questions about the kinds of models encountered in their own fields.
Video
Here are the various ways to support this work:
“Suppose the apprehension of beauty is itself a way to truth? Suppose that “elegance”—as the word is used by physicists to describe their discoveries—is a key to ultimate reality?” Rollo May
It would seem to me that any certainty arrived at must also fulfill an essential beauty or elegance in its simplicity and universal application to the understanding of what we call Reality. To my unscientific mind, most of what is termed science is unnecessarily complicated and tortured to the point that it is removed from Reality.
I wonder if it was nature doing the science and not man if things would be better explained. Like nature explaining itself using its own science.