To identify outliers in a scatter plot, you would typically look for data points that are significantly distant from the general cluster of points. Here are a few characteristics of outliers:
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Distance from Cluster: Outliers are data points that fall far away from the main group or cloud of points in the plot.
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Unexpected Values: They may represent values that are unusually high or low compared to the expected range of data.
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Visual Inspection: Outliers can often be identified by simply looking at the plot. It’s a point that does not conform to the pattern of the rest of the data.
Without a specific scatter plot to analyze, I can't provide an exact location of an outlier. However, if you have a particular plot in mind, you might consider discussing it or providing details about the data points. If you have access to statistical software or tools, you can also apply methods like the Z-score or IQR (Interquartile Range) to quantitatively identify outliers.