The correlation coefficient, often denoted as $r$, measures the strength and direction of the linear relationship between two variables. The value of $r$ ranges from -1 to +1:

• A correlation of +1 indicates a perfect positive linear relationship.
• A correlation of -1 indicates a perfect negative linear relationship.
• A correlation of 0 indicates no linear relationship.

In this context:

• A. -0.70: Indicates a strong negative linear relationship.
• B. +0.11: Indicates a very weak positive linear relationship.
• C. +1.46: This is not a valid value for correlation as $r$ must be between -1 and +1.
• D. -1.19: This is also not a valid value for correlation as $r$ must be between -1 and +1.

Given the valid options, A. -0.70 is the best result, as it has the highest magnitude of correlation (closest to -1 or +1), indicating a stronger linear relationship compared to the other valid option, B (+0.11).

Would you like more details or have any questions?

Here are 5 related questions:

1. What are the limitations of correlation coefficients?
2. How does correlation differ from causation?
3. What is the meaning of a correlation of 0?
4. What statistical tests are used to determine the significance of a correlation?
5. How does sample size affect the reliability of a correlation?

Tip: Always check the range of the correlation coefficient to ensure it falls between -1 and +1.