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The correlation coefficient between the given \( x \) and \( y \) values is approximately \(-0.986\), rounded to three decimal places. This indicates a strong negative linear relationship between the two variables.

Would you like further explanation on correlation, or have any other questions?

Here are some related questions:
1. What does a correlation coefficient of \(-0.986\) signify in practical terms?
2. How is the correlation coefficient calculated step by step?
3. Can we predict future \( y \)-values using this correlation coefficient?
4. What is the difference between correlation and causation?
5. How can outliers affect the correlation coefficient?

**Tip:** A strong negative correlation means that as one variable increases, the other decreases at nearly the same rate, but it doesn't imply causality.

Based on the data shown below, calculate the correlation coefficient (rounded to three decimal places)

Learn how to calculate the correlation coefficient for a given data set of x and y values. This problem demonstrates how to assess the strength of a linear relationship between two variables using Pearson's correlation coefficient formula. Suitable for students in Grades 9-12.

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