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The value of \( r \) in the given equation is approximately \( 0.0287 \).

Would you like a detailed breakdown of the calculation? Here are 5 related questions for further exploration:

1. What does the \( r \) value represent in statistics (such as correlation)?
2. How does changing the sample size \( n \) affect the value of \( r \)?
3. What are the implications of a small \( r \) value in a correlation analysis?
4. How do you interpret the square root portion of the formula?
5. What would happen if the sum values \( \sum xy \), \( \sum x \), or \( \sum y \) change significantly?

**Tip:** In statistics, \( r \) usually represents the correlation coefficient, which ranges between -1 and 1, indicating the strength and direction of a linear relationship between two variables.

Calculate the correlation coefficient (r) based on the given formula involving sample size and sums of products.

Learn how to calculate the Pearson correlation coefficient (r) using sample data. This problem involves calculating the relationship between variables by applying the formula for r, which is used to quantify the strength of a linear association. Detailed breakdowns of sums, square roots, and sample sizes are provided.

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