To find the correlation coefficient using technology such as GeoGebra, you would typically input the provided data points and perform a calculation to obtain the correlation coefficient (usually denoted as \( r \)).
Given the data:
- \( (2.3, 19) \)
- \( (3.1, 28) \)
- \( (4.5, 33) \)
- \( (6.6, 82) \)
You would follow these steps in GeoGebra or another statistical tool:
- Enter the data points into a spreadsheet or input them directly into the software.
- Use the correlation function or regression tools to compute the correlation coefficient.
However, without using the software directly, I can suggest that typically, the correlation coefficient (\( r \)) values range from -1 to 1. A positive value close to 1 indicates a strong positive correlation, while a value close to -1 indicates a strong negative correlation. A value around zero indicates no correlation.
Given the options you provided:
- \( 1 \)
- \( 0.88 \)
- \( 0.95 \)
- \( -0.95 \)
From a rough calculation, the relationship appears to show a strong positive trend, so one of the positive values would be correct. Typically, you would expect \( 0.88 \) or \( 0.95 \) to be likely candidates.
Since I cannot perform the calculations directly, I suggest you check and round the result to the nearest hundredth using your technology. The highest positive correlation close to one based on the data seems to align with \( 0.95 \).
Therefore, based on typical results for strong positive relationships, the most reasonable answer would be:
0.95