The development of chaos theory can be traced down from a simple mathematical inquisitiveness into a basic feature of science. It shows that even the simplest theory can show detrimental chaos meaning a random behavior without having any proper cause.

For example, in a food processor the blades follow the extremely simplistic rule, that is to say, it spins around resulting in chaos. But the food does not spin around with the blades it simply mixes up.

This type of effect can be produced in different models as well for natural phenomena.

There is a population model in biology in which every generation’s size can be easily determined by the earlier one. Theoretically, the size of a generation’s population determines the size of all succeeding generations. But in reality, hardly any real data exists. Any uncertainty grows at an exponential rate and this is why the size of any given population becomes extremely unpredictable leading to the creation of chaos.

A major impact is seen on scientific thinking. For example, the example given above shows that the meaning of deterministic and predictable is not the same.

Another example of chaos theory includes how weather forecasts are conducted. Weather is extremely deterministic by nature and very unpredictable. Due to the complex nature of weather, chaos is created hence, instead of putting all the efforts into refining and forming a single prediction, the meteorologist now forms a different type of forecast and if there is an agreement in all the types of forecasts, the prediction is most likely to be correct.

Other places in which chaos theory can be applied are the mixing of processes that are used to make medicines or the mixing of different food ingredients.