Why are curvilinear relationships hard to detect with correlation coefficients (r)?
A)Curvilinear relationships require a large amount of scores.
B)r always looks for the best straight line to fit the data.
C)r always assumes a zero association.
D)r always assumes a negative relationship.

Question

Quizplus · Accepted Answer

Correlation coefficients (r) are designed to detect linear relationships between two variables. This means that they always assume a straight line is the best fit for the data. However, curvilinear relationships would have a non-linear shape, making it difficult for r to detect this type of relationship. Furthermore, curvilinear relationships do not necessarily require a large amount of scores, so option A is incorrect. Options C and D are also incorrect because r does not assume a zero or negative relationship, but rather calculates the strength and direction of the relationship between two variables.

Why Are Curvilinear Relationships Hard to Detect with Correlation Coefficients