The problem involves interpreting the correlation coefficient, $r$, which measures the strength and direction of the linear relationship between two variables, $X$ and $Y$. In the provided question, $r = 0.91$.

The possible values of the correlation coefficient, $r$, range from -1 to 1:

• A value of 1 indicates a perfect positive linear relationship.
• A value of -1 indicates a perfect negative linear relationship.
• A value of 0 indicates no linear relationship.
• Values closer to 1 or -1 indicate a stronger linear relationship, while values closer to 0 indicate a weaker relationship.

Since $r = 0.91$ is close to 1, this suggests a strong positive linear association between the two variables.

Thus, the correct answer is:

• D. There is a strong positive linear association between the two variables.

Let me know if you want more details or have any further questions!

Here are 5 related questions to explore further:

1. What does a correlation coefficient of $r = -0.91$ imply about two variables?
2. How would you interpret a correlation coefficient of $r = 0$?
3. What are some limitations of using correlation to describe relationships between variables?
4. How is the correlation coefficient calculated from raw data?
5. Can a correlation coefficient suggest causation between two variables?

Tip: Always remember that correlation does not imply causation. Even a strong correlation doesn't mean that one variable causes changes in another.