The correlation coefficient is a statistical tool that highlights the relationship between two sets of data. Its value ranges from 1 to -1, and a strong correlation is generally considered to exist when its magnitude exceeds 0.95. A correlation close to 1 indicates similar trends in the sets, while a value close to -1 suggests opposite trends. It is important to note that correlation does not necessarily imply a cause-and-effect relationship, as other variables can simultaneously influence both sets of data.

In the fields of commerce and marketing, correlation is often used to forecast sales. For example, ice cream sales in the summer are partly related to temperatures. This illustrates the caution required before establishing a causal link based solely on correlation.