A researcher finds that the correlation between two variables is +.63, but this correlation drops to +.20 when a third variable is partialed out. In this case, the researcher should conclude that the third variable:

A) is not a factor in the correlation.
B) increases the accuracy of prediction.
C) is responsible for the original correlation between the variables.
D) does not influence the relationship between the two variables.

The fact that the correlation drops when the third variable is partialed out suggests that the third variable is responsible for the original correlation between the two variables. This suggests that there may be some spurious (or indirect) relationship between the two variables that is mediated by the third variable, meaning that the two variables may not have a direct causal relationship with each other. It is therefore important to consider the role of this third variable when interpreting the relationship between the two variables.