To estimate the correlation coefficient based on the provided data points, we need to analyze the relationship between Data 1 and Data 2.
Here’s the data:
- (0, 3)
- (2, 6)
- (4, 9)
- (6, 12)
- (8, 15)
- (10, 18)
Observations:
- The values in Data 2 appear to increase consistently as the values in Data 1 increase.
- The relationship seems to be linear as the change in Data 2 is proportional to the change in Data 1.
Calculating Correlation Coefficient:
In this case, since we see a clear positive linear relationship, we can estimate the correlation coefficient (r) to be close to 1.
Choices:
- −0.9 (negative correlation)
- −1 (perfect negative correlation)
- 1 (perfect positive correlation)
- 0.9 (strong positive correlation)
Based on the linearity and positive correlation observed in the scatter plot data, the best estimate for the correlation coefficient from the options given is 1 (perfect positive correlation).
So the response would be: 1