Which of the following best describes the strength of a linear model with a correlation coefficient $r=-0.93$?

• A. The model has a very strong positive linear relationship.
• B. The model has a weak negative linear relationship.
• C. The model has a very strong negative linear relationship.
• D. The model has no linear relationship.

Answer: (C)

Verified step by step guidance

1. Recall that the correlation coefficient \(r\) measures the strength and direction of a linear relationship between two variables, ranging from \(-1\) to \$1$.
2. Understand that the sign of \(r\) indicates the direction: a positive \(r\) means a positive linear relationship, and a negative \(r\) means a negative linear relationship.
3. Note that the magnitude (absolute value) of \(r\) indicates the strength: values close to \$1\( or \)-1\( indicate a very strong linear relationship, while values near \)0$ indicate a weak or no linear relationship.
4. Given \(r = -0.93\), observe that the value is close to \(-1\), which suggests a very strong linear relationship, and the negative sign indicates it is negative.
5. Therefore, the best description is that the model has a very strong negative linear relationship.