To solve this, we match the scatterplots with their correlation coefficients based on the strength and direction of the relationships. Here's how the correlations relate to the plots:

1. -0.90 (a): Strong negative correlation. The points form a tight downward trend.

2. 0.84 (b): Strong positive correlation. The points form a tight upward trend.

3. -0.64 (c): Moderate negative correlation. The points show a downward trend but with more spread.

4. 0.35 (d): Weak positive correlation. The points show a loose upward trend with significant scatter.

Let’s analyze each scatterplot in the image:

• First Plot: Displays a moderate negative trend. It corresponds to -0.64 (c).
• Second Plot: Shows a tight downward trend. It corresponds to -0.90 (a).
• Third Plot: Displays a loose upward trend. It corresponds to 0.35 (d).
• Fourth Plot: Shows a tight upward trend. It corresponds to 0.84 (b).

Final Matching:

1. First Plot → -0.64 (c)
2. Second Plot → -0.90 (a)
3. Third Plot → 0.35 (d)
4. Fourth Plot → 0.84 (b)

Would you like additional explanation or details about how correlations are determined?

Related Questions:

1. What are the key factors in determining the strength of a correlation from a scatterplot?
2. How can you calculate correlation coefficients from raw data?
3. What are the limitations of using scatterplots for correlation analysis?
4. What does a correlation of 0 imply about the relationship between variables?
5. How can outliers impact the correlation coefficient?

Tip: When interpreting scatterplots, focus on both the direction (positive or negative) and the spread of points (tight or loose) around a trend line.