Cause and Effect in Populations

Cause and Effect in Populations is a very useful topic. Cause in populations is defined as “a claim that If the cause is present, there is a higher probability the effect will follow than if the cause were not present(Epstein 392)”. The example in the book is that smoking lots of cigarettes over a long period of time will cause a higher probability that it’ll cause lung cancer. We know that if you do something, there will be an outcome or effect by it. There is a problem with cause and effect that we actually don’t have an idea nor is it likely that we can state normal conditions for smoking. The one thing that we can do in cause and effect is to point out the evidence that we do have that convinces us that’s the effect of causing something, such as smoking or drunk driving. Evidence must be present in order to have a cause an effect scenario.