To answer the question about the scatterplots:

Analysis of the Scatterplots:

1. Plot (1):
   • The points are tightly clustered in a downward sloping pattern.
   • This suggests a negative association with a very strong relationship because the data points are closely aligned.
2. Plot (2):
   • The points appear randomly scattered with no discernible pattern.
   • This indicates little or no association.
3. Plot (3):
   • The points follow a downward slope but are not as tightly clustered as in (1).
   • This suggests a negative association that is moderately strong.
4. Plot (4):
   • The points loosely follow an upward trend, indicating a positive, weak association.

Answers to Each Part:

a) Little or no association: Scatterplot (2).
b) Negative association: Scatterplots (1) and (3).
c) Linear association: Scatterplots (1), (3), and (4).
d) Weak or moderately strong association: Scatterplots (3) and (4).
e) Very strong association: Scatterplot (1).

Would you like more details on how these patterns are identified? Here are some related questions for further understanding:

1. How do you mathematically measure the strength of association in a scatterplot?
2. What are the key differences between strong and weak linear associations?
3. Can a scatterplot show a curvilinear relationship, and how would that affect interpretation?
4. What statistical tools can be used to quantify the slope of associations seen in scatterplots?
5. How can outliers affect the strength and direction of the association in scatterplots?

Tip: Always look for patterns in scatterplots—whether upward (positive), downward (negative), or random scatter (no association)—and assess how tightly points cluster around a trend line.