Random thoughts about Randomness; the math of random numbers

When you don't understand exactly what causes something to happen, you try to develop some insight into what you do understand to at least get more information to work with when making decisions regarding the issue.

The problem is when you don't understand the difference between correlation and causation, to the point that you have a factual correlation between different 'factors,' and instead of thinking critically about how two correlated factors could be causally related, you just assume that the antecedent factor causes the other one without thinking about how the causation does or might work at the mechanical level.


Lots of social science uses statistics to find correlations and other patterns in data. It not worthless, but it is what it is and what it's not is causal-mechanical analysis. A major problem among people who become familiar with statistical logic is that they begin dismissing the significance of causal mechanics completely. This is just hubris based on the fact that when you learn to work with statistics and are successful with it, you don't want to be confronted with causal-mechanical logic that is more difficult and not as easy to test.

E.g. if you start studying cancer and how cells mutate, spread, etc. it is very easy to get overwhelmed by the massive complexity of biological and/or ecological systems. When you are trying to make sense of complex systems, you have to be able to use what some call 'fuzzy logic' to take account of complexities in a less-than-exact way without either discounting them completely or assuming that you have them nailed down. That is hard for people who are used to working with numbers and math that produce absolutely clear quantitative-logical results, regardless of how well the quantification of empirical systems and/or analytical logic of the mathematical processes/procedures work vis-a-vis the realities they are supposed to model.

So you end up with strange phenomena in quantitative analytics where certain equations and mathematical processes/procedures result in models and logics that fit the data together in very accurate ways that provide a sense that a true explanation has been found; but in reality, you have just tricked the mind into accepting that there's no further explanation needed or possible, i.e because 'the numbers work.'

That is basically what you're doing when you flip a coin or roll dice thousands of times and show statistically that the probability ratio approaches 50/50 (i.e. 1 in 2) or 1 in 6 or 1 in 36, etc. It is very satisfying to figure out that you can multiple 1/6 by 1/6 and get 1/36 as the probability of a pair of six-sided dice landing in a given combination of sides, but then the temptation is to assume that is the whole story and "nothing more to see here." But reality is more complex than quantifying and mathematically analyzing things you deem countable.


And it could very well be important, but the question is not what "most people would consider" but why and how it's important, if it is; or why it's not important, if it's actually not.


Everything that happens occurs because of specific chains of causation. When you find patterns of similarity/regularity, you might think there's nothing specific or unique about the way a common event is caused, but that doesn't mean that it doesn't have a specific chain or web of events and conditions that caused it.


The way you state it here implies that there is randomness in nature, but randomness is not something fundamental about reality but rather something that emerges at certain levels of analysis.

Take for example a pot heating up water on a stove. You could say that as the bottom of the pot heats up, it transfers energy randomly to the water molecules in the pot, but if you look closer, it really only transfers energy to those molecules touching the bottom and/or touching other parts of the pot that absorb infrared going through the water. Then you might say even if there are convection currents circulating inside the pot to move the hotter water around and mix it with the cooler water, that mixing is random; but again if you could look closely enough, you would see that each molecule undergoes specific momentum-change and interacts with specific constraints that shape its movement and behavior relative to its surroundings.

So although systems can be complex beyond our ability to keep track of all the complexities, they are still made up of causal-mechanics and not 'random chance.' 'Random chance' is a probabilistic statement that compares the likelihood of some event or trait being found in the individuals of a population. E.g. you might ask whether it is random chance whether a given molecule of water will end up rising out of a boiling pot as steam if it begins on the left or right side of the pot when the pot is still cold. It might turn out that the relationship between which side of the pot the water is on and whether it ends up as steam or not is random, but that doesn't mean the events that cause a given molecule of water to become steam are random.

You are being ridiculous again Lava.

We don't know why mass has gravity (we have come up with this thing called a graviton, but we have know idea of the "why"). Yet, when I am sitting at my desk, and drop this pen... I am 100% confident that it will drop to the floor (in fact, I just did it and it worked). And I will go further and say that gravity is the cause of this pen dropping.

You seem to have a problem with this. There are lots of examples of this. In your billiard ball example the balls are repelled by electronic force (no particle of one billiard ball ever touches the other). We have no explanation for the electronic force, it just works that way. And yet even you use this as an example.

I have already explained to you that we can test for, and establish, causation through experiments. Correlation doesn't mean causation, but a double blind experiment does.

This idea that you must reject anything you don't understand is ridiculous. The smartest, most knowledgeable humans on the planet don't have a good explanation for the fundamental forces. We would have to reject everything.

You are attempting to deny everything I've explained about causal mechanics by making a philosophical argument about gravity and you call me ridiculous?

Here's a simple reason you might be able to understand why statistics doesn't really explain anything: it doesn't work with small populations/sample sizes well and it doesn't work at the individual level at all.

e.g. if you look at an entire city or area of a city, you might be able to correlate the lights going off with the sun coming up or with a power outage or some other external stimulus, but if the lights go off in a single room, you don't know whether it was caused by a power outage, the circuit breaker failing, the light bulb burning out, or maybe someone just flipped the switch, and you also don't know why they flipped the switch; e.g. to conserve energy, because they wanted it darker, to see a screen better, etc.


If you want to discuss what may or may not be the cause of gravity, start a different thread on it. It's a bad example because there are different theories and people argue about how to interpret those theories.


Causation is simply not addressed by statistical analysis. Causation occurs at a mechanical level, while statistics deal with probabilities of outcomes relative to potential causes.

Simple example: let's say you have a totally racist criminal justice system where everyone who's in jail is one race and no one identified as the other race is ever jailed due to racial favoritism. In that case, you have an exact statistical correlation between race and incarceration, but you know nothing about the cause. Some people will argue it's pure coincidence and others will argue it's pure racial bias, but the reality is that each person ended up in jail because of a specific chain of events that might have involved racism in various ways, as well as criminal behavior/choices in other ways. This is actually a good example because criminal behavior and discrimination are not mutually exclusive factors except by a certain statistical logic that ignores how reality works at the causal level. At the causal level, someone can face discrimination, try to resist cooperating with criminal organizations, and finally give in out of desperation, and be chosen for a particularly risky crime to commit instead of one that's easier to get away with because of racial prejudice within the organization.

Statistical logic defies understanding of deeper complexities that actually cause reality to happen in specific ways in various situations.

I am still thumbing up Lava even though I disagree with him. But let's move on.

Years ago, Apple had a problem with the random play feature of their ipod shuffle. The Apple engineers swore that songs were being played at random. There was no mathematical evidence that the songs weren't being played at random. Yet customers kept noticing patterns in the songs being played. The customers claimed that songs were being played too often, or that they were certain that some types of songs were favored over other types of songs.

Apple received a lot of complaints about how their random play feature wasn't really random. What was the obvious solution.... They made the random play feature less random. Instead of truly randomizing the songs, the engineers made sure that there were no repetitions and that different genres of songs were represented in a non-random way. I believe that this made people happy. On some Apple ipods they even added a feature called "avoid repetitions" which made the song selection less random.

Humans are very bad at detecting randomness. When humans create random numbers by imagination, it is easy to show mathematical patterns. Human beings see repetition as non-random, and so repeating data is underrepresented in human-generated random data. Likewise, if I gave a human being four pages of data, and asked them to tell me which is random... they would likely get it wrong.

Mathematically... if we have a large amount of data, we can ask the question "what are the odds that this data is the result of a random process?". Data that is highly unlikely to be random is interesting. You probably have heard about SETI (the search for extraterrestrial intelligence). This math is as at the core of it.

This post is not a response to anything in the previous post of mine it's in response to, so I don't understand why you posted it as a response.

Obviously It is because I pushed the "reply" button. (If you understood causation you would understand this). But the question is the "underlying reality" or the mechanical "causation" behind it.

With Bayes' Theory, we could calculate the probability that this was just random behavior on my part (which seems like a reasonable possibility). If we calculate that this is very unlikely to happen randomly, then you can assume that there is something else behind it.

It is possible that I am just ******* with you.

Don't waste my time.