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The question is asking which value indicates a strong negative correlation. Correlation coefficients (denoted by *r*) range from -1 to +1:

- **Positive correlation** is indicated by values closer to +1.
- **Negative correlation** is indicated by values closer to -1.
- A value near 0 suggests no correlation.

A **strong negative correlation** occurs when *r* is closer to -1. 

In this case, the options are:
- (a) r = 0.54 (positive and weak correlation)
- (b) r = 0.982 (positive and very strong correlation)
- (c) r = -0.793 (moderate negative correlation)
- (d) r = -0.859 (strong negative correlation)

The correct answer is **(d) r = -0.859**, since it is closest to -1 and indicates a strong negative relationship.

Would you like more details or have any questions? Here are 5 related questions to expand on this topic:

1. What does an *r* value of -1 imply in a dataset?
2. How is the correlation coefficient calculated in statistics?
3. Can a correlation imply causation? Why or why not?
4. What are the limitations of correlation analysis in research?
5. How can you visually represent correlation in a scatterplot?

**Tip:** A correlation coefficient near ±1 implies a stronger relationship, but it doesn’t explain the nature of the cause-effect relationship.

Which of the following indicates a strong negative correlation?

Explore what constitutes a strong negative correlation with an example where r = -0.859. This page explains how correlation coefficients range from -1 to +1 and how values closer to -1 signify a strong negative correlation, ideal for college-level statistics courses.

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