What is the purpose of the correlation coefficient?

The correlation coefficient is a statistical measure used to assess the strength and direction of a linear relationship between two variables. When calculating the correlation coefficient, you obtain a value that ranges from -1 to +1. A value close to +1 indicates a strong positive relationship, meaning that as one variable increases, the other tends to increase as well. A value close to -1 indicates a strong negative relationship, suggesting that as one variable increases, the other tends to decrease. A value around 0 implies little to no linear correlation between the variables.

This coefficient is essential in fields such as business statistics, where understanding the relationship between different factors can influence decision-making and strategy development. For example, if a business wants to analyze the relationship between advertising spend and sales revenue, the correlation coefficient can provide valuable insight into how these two variables are associated.

In contrast, determining an average value, calculating variance, or visualizing data distributions focus on different aspects of statistical analysis that do not specifically address the relationship between two variables. Thus, the correlation coefficient serves a unique purpose that is accurately captured by the selected answer.