# Understanding Random

People like to use the term random without actually really understanding what random means. The term random simply means an event has so many variables or inaccessible variables that it can’t be fully understood. Random is ignorance of the variables involved. When the variables of a situation can’t be accessed for one reason or another, science resorts to using statistical models. If a statistical model has any degree of success it is because it is picking up on constants indirectly.

In an attempt to explain the order in chaos I have built a new project which ca be accessed by clicking below.

Click Image Below To Launch Project

Essentially what this project does is take a series of very standard waves and combines them to build a more complex wave form. You can play around with the different settings to get all kinds of interesting wave forms.  The more waves you add and change, the more complex the final form will become. If you were not aware of all the different waves that went into creating the final form, you would have a very difficult time trying to figure out how it was created.

Another example would be to drop a dice down a very small tube and then slowly increase the size of the tube on additional rolls. As the tube got larger it would become increasingly difficult to predict how the dice would land. In the same way, in the above wave example it might be easy to guess or predict a wave form if it is only made up of two waves, but it would become increasingly difficult to predict as you added more.

The problem is that because random activity is built on orderly components, it can sometimes mislead us to believe we can predict it. In real life we have another name for it, we call it luck. What we consider luck is more a product of timing than any innate characteristic that gives us an upper hand. There will always be the temptation of trying to figure out how things work by looking at a final form, but we must aggressively resist this seduction. We can only gain true understanding by analyzing the underlying orderly components, not the final production.