What is the purpose of a correlation coefficient?

The purpose of a correlation coefficient is to measure the strength and direction of the relationship between two variables. This statistical measure quantifies how strongly two variables are related and whether they move together in a positive or negative way. A positive correlation indicates that as one variable increases, the other tends to also increase, while a negative correlation suggests that as one variable increases, the other tends to decrease. The value of the correlation coefficient ranges from -1 to +1, where values close to +1 indicate a strong positive relationship, values close to -1 indicate a strong negative relationship, and values around 0 imply no significant relationship between the variables.

The other choices do not encompass the purpose of a correlation coefficient. Determining the mean and calculating the median relate to measures of central tendency, which summarize data by finding an average or middle value rather than exploring relationships. Comparing datasets with different scales involves techniques like standardization or normalization, which are distinct from the purpose of a correlation coefficient.