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The correlation coefficient \( r = 0.91 \) indicates a **strong positive linear association** between the two variables. Since the value of \( r \) is close to 1, this suggests a strong relationship, and because it's positive, the association is positive.

Thus, the correct interpretation is:

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

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### Related Questions:
1. What is the range of possible values for the correlation coefficient \( r \)?
2. How do you interpret negative correlation coefficients?
3. What does a correlation coefficient of 0 signify?
4. Can a correlation coefficient indicate causality between variables?
5. How would you calculate the correlation coefficient from a dataset?

### Tip:
A correlation coefficient close to 1 or -1 indicates a strong relationship, while a value close to 0 indicates little to no linear relationship.

Values of X and Y were recorded for an additional three weeks, and the correlation coefficient, r, for the augmented data set was found to be r = 0.91. Which of the following statements best interprets this result? A. There is a weak positive linear association between the two variables. B. There is a weak negative linear association between the two variables. C. There is a strong negative linear association between the two variables. D. There is a strong positive linear association between the two variables.

Explore the interpretation of a correlation coefficient r = 0.91, indicating a strong positive linear association between two variables. This problem highlights key statistical concepts and the Pearson correlation coefficient formula, suitable for students in Grades 10-12.

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