To interpret a scatterplot, you would typically look for patterns in the data points plotted on the graph. Here's how to classify the association based on common patterns:
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Linear Association: If the points form a pattern that resembles a straight line (either upwards or downwards), then the association is linear.
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Non-linear Association: If the points create a curve or another kind of non-straight line (e.g., quadratic, exponential), then the association is non-linear.
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No Association: If the points are scattered randomly without showing any discernible pattern, then there is no association.
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Negative Association: If the points trend downwards (as one variable increases, the other decreases), this indicates a negative association.
Without a visual representation to assess, it's difficult to determine the correct classification. If you describe the pattern or the orientation of the points, I can help you better interpret the type of association!