Correlation is a statistical measure that describes the strength and direction of the relationship between two variables. In a correlation analysis, there are typically two variables involved. These variables are referred to as "co-variables" or "correlates" because they are being examined together to determine the relationship between them.

Co-variables in a correlation analysis:
Co-variables in a correlation analysis refer to the two variables that are being examined to determine if there is a relationship between them. These variables are not labeled as dependent or independent variables in correlation analysis. Instead, they are both considered as co-variables because the purpose is to assess the relationship between them.

Explanation of the options:
a) Dependent variables: In correlation analysis, there is no specific dependent variable. Both variables are being examined together to determine their relationship, so it is not appropriate to label one as dependent and the other as independent.

b) Independent variables: Similarly, there is no specific independent variable in correlation analysis. Both variables are being examined together, and the focus is on assessing the relationship between them rather than determining causality.

c) Co-variables: This is the correct answer. Co-variables refer to the two variables being examined in a correlation analysis. They are both considered equally important, and the goal is to determine the strength and direction of their relationship.

d) Dependent and independent variables: While these terms are commonly used in other statistical analyses such as regression, they are not applicable in correlation analysis. Correlation analysis focuses on assessing the relationship between two variables without distinguishing them as dependent or independent.

Conclusion:
In a correlation analysis, the variables being examined are called co-variables. They are both considered important and are assessed together to determine the strength and direction of their relationship. It is important to understand the terminology and concepts used in correlation analysis to accurately interpret and communicate the results.