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The image contains four scatter plots labeled as Figure 1 through Figure 4 and three corresponding questions. Here's an interpretation of the questions and how to approach them:

1. **Which data set has an apparent positive, but not perfect, linear relationship between its two variables?**
   - Look for a scatter plot where the data points show a general upward trend (i.e., as one variable increases, the other tends to increase) but does not form a perfect straight line.

2. **For which data set does the correlation coefficient \( r \) appear to be equal to -1?**
   - The correlation coefficient \( r \) is -1 when there is a perfect negative linear relationship, meaning the points lie exactly on a straight line with a negative slope.

3. **Which data set indicates the strongest linear relationship between its two variables?**
   - Identify the scatter plot where the points are closest to forming a straight line, whether positive or negative.

### Answers Based on the Scatter Plots:

- **Figure 1**: Data points seem scattered with no strong relationship, probably no linear correlation.
- **Figure 2**: Shows a strong negative linear relationship, where the points are nearly on a straight line. This would likely have \( r = -1 \).
- **Figure 3**: Also shows a negative linear trend but less tight compared to Figure 2. Still a moderately strong negative correlation.
- **Figure 4**: Displays a weak positive linear trend, where the points are spread out but generally increasing.

### Suggested Answers:

1. **Positive, but not perfect, linear relationship**: Figure 4.
2. **\( r = -1 \)**: Figure 2.
3. **Strongest linear relationship**: Figure 2.

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### Related Questions:
1. How do you calculate the correlation coefficient \( r \) mathematically?
2. What does a positive or negative correlation coefficient signify?
3. How can outliers affect the correlation coefficient?
4. What is the difference between a strong and weak linear relationship?
5. How can you use the line of best fit to estimate correlation strength?

### Tip:
A correlation coefficient of \( r = 1 \) means a perfect positive linear relationship, while \( r = -1 \) indicates a perfect negative one.

Shown below are the scatter plots for four different data sets. Answer the following questions: 1. Which data set has an apparent positive, but not perfect, linear relationship between its two variables? 2. For which data set does the correlation coefficient r appear to be equal to -1? 3. Which data set indicates the strongest linear relationship between its two variables?

Understand how to interpret scatter plots and calculate correlation coefficients from data sets. This example includes scatter plots from four different data sets, asking you to identify positive linear relationships, and determine which data set has a correlation coefficient of -1. Perfect for high school students studying statistics.

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