Based on the data provided, we can analyze the points in each table to identify whether the association between the x and y values is linear or non-linear.
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First Table:
- x: 50, 46, 80, 59, 78, 64, 68, 53, 70, 68
- y: 35, 30, 75, 45, 70, 50, 55, 36, 62, 67
- The scatterplot likely shows a weak positive trend in certain ranges but is not consistent, indicating potential non-linearity.
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Second Table:
- x: 50, 46, 98, 59, 78, 64, 68, 53, 70, 72
- y: 75, 71, 90, 55, 70, 100, 90, 25, 40, 76
- This table depicts a more varied y response at different x values, suggesting a non-linear association.
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Third Table:
- x: 50, 46, 80, 59, 78, 64, 68, 53, 70, 68
- y: 90, 100, 57, 80, 60, 75, 72, 82, 70, 67
- The data shows more variation with response y values not following a consistent pattern as x increases, hinting towards non-linearity.
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Fourth Table:
- x: 50, 46, 90, 59, 78, 64, 68, 53, 70, 72
- y: 75, 71, 100, 80, 90, 82, 85, 77, 87, 89
- This set of data appears to show a clearer linear trend as y values increase with x.
Conclusion:
After looking at the trends described from the data in each table, the second and third tables most likely depict non-linear associations due to the scatter of y values not consistently increasing or decreasing with corresponding x values. However, the second table appears to have a more significant and varied dispersion indicating a clear non-linear association.
If you are only to select one, the second scatterplot is the best candidate showing a non-linear association.