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Question
screen time vs study time
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question 2
which of these points appears to be an outlier in the scatterplot?
(2.6, 6.8)
Step1: Understand the concept of an outlier
An outlier in a scatter - plot is a data point that significantly deviates from the general pattern of the data.
Step2: Analyze the scatter - plot pattern
Looking at the "SCREEN TIME VS STUDY TIME" scatter - plot, most of the data points follow a decreasing trend (as study time increases, screen time decreases). The point \((4,9.5)\) (assuming this is the non - conforming point based on the general trend of the scatter - plot, although it's not in the given options. But if we assume the options are mis - labeled and we go by the visual pattern):
If we consider the general trend of the scatter - plot (a negative correlation where screen time decreases as study time increases), we check each point.
For a point \((x,y)\) (where \(x\) is study time and \(y\) is screen time), in a negative - correlated data set, as \(x\) increases \(y\) should decrease.
If we assume the non - optioned point (by visual inspection of the scatter - plot, the point with \(x = 4\) and \(y\approx9.5\) is far above the general trend of the other points. While for \((2.6,6.8)\), it follows the general decreasing trend of the data points (as \(x = 2.6\) is relatively small and \(y=6.8\) is relatively large which is in line with the negative correlation pattern of the majority of points).
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If we assume the options are incorrect (based on visual inspection of the scatter - plot, the outlier is the point with \(x = 4\) and \(y\approx9.5\)). But if we strictly go by the given option \((2.6,6.8)\) is not an outlier as it follows the general trend of the scatter - plot (negative correlation: lower \(x\) (study time) with higher \(y\) (screen time)). There might be a mis - representation of options. If we assume the intended outlier is based on the visual scatter - plot (not the given option \((2.6,6.8)\)), the outlier is the point with \(x = 4\) and \(y\approx9.5\) (a point that does not follow the negative - correlation trend of the majority of data points).