Let's analyze each scatterplot and answer the questions based on the associations shown:

1. a) Little or no association: Scatterplot (3) shows little or no association because the points do not appear to follow any clear pattern, indicating a weak or nonexistent relationship between the variables.

2. b) A negative association: Scatterplots (1) and (2) show a negative association, where the points generally decrease in value as they move from left to right, indicating a negative correlation between the variables.

3. c) A linear association: Scatterplots (1) and (2) exhibit a linear association. In both cases, the points follow a roughly straight-line trend, indicating a linear relationship.

4. d) A weak or moderately strong association: Scatterplot (2) likely shows a moderate association. Although it is negative and somewhat linear, the points are more spread out compared to Scatterplot (1), which suggests a weaker association.

5. e) A very strong association: Scatterplot (1) shows a very strong association. The points are tightly clustered around a negative linear trend, indicating a strong linear correlation.

Would you like further details on any of these interpretations?

Here are some related questions to deepen your understanding:

1. How can you quantify the strength of an association in a scatterplot?
2. What statistical measures can confirm the type of association (positive or negative)?
3. How does outlier presence affect the perceived association in scatterplots?
4. What is the role of correlation coefficients in determining association strength?
5. Can a scatterplot with a curved trend still indicate a strong association?

Tip: When analyzing scatterplots, look at the overall direction, strength, and form of the points' distribution to determine the type and strength of association.