What does random mean?

Since my essay series had been unceremoniously thrown into the Random category, I thought it would appropriate to give you my thoughts on the concept of randomness.

If my series is random it doesn’t follow that genre because it’s mostly about science with a bit of science fiction and religion thrown in. However, be that as it may, I will go on.

Most people think that random means just a lack of predictability, but, like the concept of infinity, it has mathematical definitions depending on the branch of science or mathematics that employ it.

Probably the field that uses randomness the most is statistics. In order for a process to be random the method of creating a random sample dictates that the elements of the random sample be chosen randomly. This sounds like a circular argument, but it has serious importance in a computer program that’s being used to generate random numbers.

Think about it this way. If you use a coin to determine how often heads or tails will be selected when you flip the coin in the air (like they do at the start of an NFL game) random selection should give you a 50 % chance for both heads and tails if you do it enough times. In other words, chance predicts that it will be a 50:50 probability. Statistics assumes that the method of selecting data is completely random, but it seldom is. There’s always some bias involved.

How does one create random numbers? This is very important concept if one wants to write an algorithm to create random numbers for a computer game. There are several methods to generate random numbers. The Monte Carlo method uses several ideas, one being a so-called pseudorandom number generator. These generator progrmas are used for computer games, simulations, genetic evolution predictors, weather predication and a host of other applications. Basically, a pseudorandom number generator uses mathematical equations with seed numbers to calculate a random number. The seed number could come from the number of bits in noise (number) generated in the processor chip at any given time. The exact process differs depending on the computer operating system, but these algorithms are built into operating systems, and for the most part they are quite good at creating pseudorandom numbers.

The big question is: how random are these pseudorandom generated numbers? That’s a good question, but the answer varies. One thing is for sure; the random numbers generated by these programs are not perfectly random. They suffer from poor dimensional distribution and lack of uniformity. These are important factors if one is trying to generate a secure password. In other words, a pseudorandom number may not be cryptographically secure. For example, the launch codes for nuclear missile are generated randomly on a regular basis. The idea here is to prevent someone, or some advanced computer system, from breaking the random algorithm and determining the codes like in the 1983 movie ‘War Games’ starring Mathew Broderick. Think about that!

For most applications, pseudorandom number generators are good enough. For example, your Call of Duty game uses randomness to determine how your enemy might attack you. The randomness here is close enough.

Thanks for reading.