Final answer:
The correlation between bear age and weight is likely to be a positive correlation, where the age and weight of a bear increase together. The significance of the correlation is determined by the value of the correlation coefficient, with values closer to 1 indicating a strong, significant relationship.
Step-by-step explanation:
The correlation between bear age and weight is likely to be a positive correlation, meaning that as the age of a bear increases, its weight also tends to increase. The magnitude and sign of the correlation coefficient reflect this. A positive correlation coefficient, which is between 0 and 1, indicates that the variables are directly related and move in the same direction.
In determining whether the correlation is significant, you would look at the value of the correlation coefficient. If this value is close to 1 or -1, the relationship is strong, and therefore the correlation is likely to be significant. A very low correlation coefficient, closer to 0, would indicate a weak or non-existent relationship.
To specifically address the questions:
- Whether the correlation is significant can be deduced from the value of the correlation coefficient, which indicates the strength of the relationship between the variables. A correlation coefficient near 1 or -1 implies a significant relationship.
- The relationship between bear age and weight is positive, as both variables tend to increase together. This can be determined by looking at the direction of the slope in a scatter plot or the sign of the correlation coefficient.