To identify the outlier among the points mentioned, we need to analyze the distribution of the data points and see which one doesn't fit the general pattern.
From your description, the scatterplot has a loosely packed cluster of data points between heights of 60 to 64 inches and weights of 115 to 135 pounds.
Now, let's evaluate the points provided:
- (60, 123): This point falls within the cluster.
- (61, 95): This point has a weight that is significantly lower than the cluster, making it an outlier.
- (64, 125): This point also falls within the cluster.
- (63, 122): This point falls within the cluster too.
Based on this analysis, the outlier is (61, 95), as it deviates significantly from the other points in that area.