To accurately interpret the type of association shown in a scatterplot, you would typically look for patterns in the data points. However, since I cannot see the scatterplot you're referring to, I can explain how to identify the types of associations.
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Linear Association: If the data points tend to follow a straight line (either positively or negatively), you have a linear association.
- Positive Linear: As one variable increases, the other variable also increases.
- Negative Linear: As one variable increases, the other variable decreases.
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Non-linear Association: If the data points follow a curve or any shape other than a straight line, the association is non-linear.
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No Association: If the points are scattered randomly without any discernible pattern, there is no association between the variables.
Based on your choices:
- Select non-linear association if the points follow a curved pattern.
- Select no association if the points do not form any specific pattern.
- Select negative association if the points form a downward trend.
- Select linear association if the points form an upward or downward straight line.
Please evaluate the scatterplot based on these descriptions to choose the correct answer.