https://file.aiquickdraw.com/mathbot/file/17259507761271s4llbvs.jpg

To match each scatterplot with the correct correlation coefficient, let's analyze the general pattern of each scatterplot and the possible values for the correlation:

The given correlations are:
- a. -0.29
- b. 0.53
- c. -0.91
- d. 0.97

### Analysis of Scatterplots:

1. **First Scatterplot (Top)**
   - The data points seem to have a **strong positive linear relationship**. The points are closely clustered around an upward slope. This indicates a correlation close to +1.
   - **Match:** d. 0.97

2. **Second Scatterplot (Second from Top)**
   - The points are **loosely scattered** with no strong pattern, but there is a slight downward trend. This suggests a weak negative correlation.
   - **Match:** a. -0.29

3. **Third Scatterplot (Second from Bottom)**
   - The points are **strongly clustered** around a **negative linear trend**, indicating a high negative correlation.
   - **Match:** c. -0.91

4. **Fourth Scatterplot (Bottom)**
   - The points display a **moderate positive linear relationship**, but they are more spread out compared to the first scatterplot. This indicates a moderate positive correlation.
   - **Match:** b. 0.53

### Conclusion:
- **First scatterplot:** d. 0.97
- **Second scatterplot:** a. -0.29
- **Third scatterplot:** c. -0.91
- **Fourth scatterplot:** b. 0.53

Would you like further details or have any questions?

### Related Questions:
1. What is the meaning of correlation coefficient values between -1 and 1?
2. How can you visually determine if a correlation is positive or negative?
3. What are some common real-life examples of positive and negative correlations?
4. What does a correlation coefficient close to 0 signify?
5. How do outliers affect the correlation of a dataset?

### Tip:
Correlation does not imply causation. Even if two variables show a strong correlation, it doesn't mean that one causes the other to change.

Match each scatterplot shown below with one of the four specified correlations: a. -0.29, b. 0.53, c. -0.91, d. 0.97.

Analyze and match each scatterplot with the correct correlation coefficient, ranging from -0.91 to 0.97. This problem demonstrates how to visually interpret correlation strength and direction through statistical data representation. Suitable for high school students studying correlation and scatterplot analysis.

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