To calculate the correlation coefficient \( r \) using the provided data, you can typically use software or an online calculator like GeoGebra.
Here's how you can interpret the possible responses:
- 0.94
- 0.93
- 0.90
- 6.40 (which is likely incorrect, as correlation coefficients are typically between -1 and 1)
Based on the potential values and rounding conventions, it is common for a dataset like the one you provided to yield a correlation coefficient that falls around 0.90 to 0.94 if there is a strong positive linear relationship.
If you have access to GeoGebra or another tool, inputting the \( x \) and \( y \) values will provide the correlation coefficient. Based on typical outputs of such datasets, I would estimate the value to predominantly be:
0.93
This value indicates a strong positive correlation between the x-values and the y-values.