While a relationship between two variables may be observed, it is not enough to say that there is a casual relationship whereby one variable causes a change in the other. 

Examples:

1. A study of primary school children found a high positive correlation between shoe size and reading ability. Thus there is a physical cause for some students’ reading problems. Alternative explanation: Age is a stronger factor. Older children tend to have larger feet and more time to learn how to read.
2. A study of health care numbers found a high positive correlation between the number of doctors in a city and the number of sick people. It is concluded that we should have fewer doctors. Alternative explanation: larger population gives rise to a greater number of sick people, and hence more doctors to tend to them.

See more:

• Patterns represented in scatterplots