I'm just saying, campaign your hearts out and you can have a huge impact on political races, but when it comes time to cast your own vote, it's insignificant. Far too many people are too hyped up about their own vote, but if you don't bother to enter into the politcal process, you're deluding yourself if you think the act of casting a vote matters.
Another important aspect in dealing with systems is that systems can be modeled. In other words, systems can be created which will theoretically replicate the behavior of the original system. Following the pile of stones example, one could take a second group of stones which are identical to the first group, pile them in exactly the same way as the first group, and predict that they will fall down into the exact same configuration as the first group. Similiarly, a mathematical model, based upon Newton's law of gravity, could be used to predict how piles of same and different types will interact. Generally speaking, mathematical modeleing is the key to modeling systems, although it is not the only way.
The second term, nonlinear, has to do with the type of mathematical model used to describe a system. Until the recent growth of interest in chaos theory, hence nonlinear systems, most models were analyzed as though they were linear systems. In other words, when the mathematical models were draw in a graph format, the results appeared as a straight line. Calculus was Netwon's mathematical method for showing change in systems within the context of a straigt line and statistics, regression analysis in particular, is a process of converting nonlinear data into a linear format for further analysis and prediction.
Linear systems are easy to generate and simple to work with. That is because they are very predictable. For example, you could think of a factory as a linear system. We could predict that if we add a certain number of people, or a certain amount of inventory to the factory, that we will increase the number of pieces produced by the factory by a comparable amount. As most managers know, factories don't operate this way. Changing the number of people, inventory, or any other variable in the factory and you receive widely differing results on a day to day basis from what would be predicted from a linear model. This is true because a factory is actually a nonlinear system, as are most systems found in life. When systems in nature are modeled mathematically, we find that their graphical representations are not straight lines and that the system's behavior is not so easy to predict.
Did I pass the audition?
