D. Correlation

Explanation:

1. Correlation is a statistical measure that expresses the extent to which two variables are linearly related. It measures both the strength and direction of the relationship between two variables.
2. Regression is used to predict one variable based on another, but it doesn’t directly measure the degree of association.
3. Percentiles divide a set of data into 100 equal parts, but don’t measure association between variables.
4. Quartiles divide a set of data into four equal parts, but don’t measure association between variables.
5. Coefficient of variation measures the relative variability of a single variable, not the association between two variables.

Correlation is typically expressed as a correlation coefficient, which ranges from -1 to +1. A correlation of +1 indicates a perfect positive relationship, -1 indicates a perfect negative relationship, and 0 indicates no linear relationship between the variables. Therefore, correlation is the correct measure to determine the degree of association between two variables.