What are correlations used to measure?

Correlations are specifically used to measure the relationship between two numeric variables. When performing correlation analysis, the primary goal is to ascertain how one variable may change in relation to another, indicating whether an increase in one variable is associated with an increase or decrease in the other. This relationship can be quantified using a correlation coefficient, which ranges from -1 to 1, where values close to 1 indicate a strong positive correlation, values close to -1 indicate a strong negative correlation, and values around 0 suggest no correlation.

In contrast, the other choices pertain to different analytical concepts. Total data in a dataset pertains to measures of data volume, while the frequency of categorical responses relates to categorical data analysis, and the distribution of a single variable over time describes trends or changes within that specific variable rather than exploring the relationship between two variables. Therefore, the focus of correlation analysis is distinctively on understanding the interdependency between numeric data sets.