To determine if there is an outlier in the scatter plot, we need to evaluate the given points based on their distribution.
- (6, 60): This point has a relatively high y-value compared to its x-coordinate.
- (60, 6): This point has a very high x-value but a comparatively low y-value.
The two points seem to be at extreme ends based on their axes. However, to identify whether they are truly outliers, we would typically look at the overall distribution of other data points on the scatter plot.
- If the majority of points are clustered together around a specific area, then either or both of these points could be considered outliers.
- If the distribution of points is more or less even across the area of the plot, then there may not be a clear outlier.
Based on the two points provided and their positions:
- (6, 60): When plotted, this would be a point that could be above a trendline if most other points are lower.
- (60, 6): This could be seen as somewhat isolated in the opposite direction, especially if most other points have lower x-values.
Given that we have no other context or points from the scatter plot, if we consider extreme variations in coordinates:
- The point (6, 60) could be an outlier if all other points are more clustered in lower y-values.
- The point (60, 6) could also be an outlier if most points are clustered at lower x-values.
Thus, based on just the provided points, it’s reasonable to suggest either (6, 60) or (60, 6) could be an outlier. If forced to choose without more context, perhaps the more extreme value from the average trends would be marked as an outlier.
If you have access to the actual scatter plot, evaluate the surrounding points to make a final determination. If you are looking for a definitive answer with no additional context provided, then you might conclude that there are outliers here, possibly (6, 60) or (60, 6), depending on the overall distribution of the other points. If the responses suggest No outlier, it implies the overall dataset does not show extreme variation from these points.
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