There is no substitute for a well- designed experiment. As a result, it is more difficult to draw conclusions about cause and effect. The text looks at several examples, including smoking, clofibrate, and pellagra. In the smoking example, the hypothesis is that smokers have an increased risk of becoming sick. We see that merely comparing sickness rates for smokers and nonsmokers is too simplistic because the groups differ in other ways than smoking.
Smokers tend to be older than nonsmokers, for example.
This makes age a confounding factor . It is possible that the increased sickness is due to age, not smoking. To control for this factor, the investigator could compare sickness rates among smokers and nonsmokers of similar ages. However, other unkown factors might cause the sickness. In an observational study, you can only show associations.