We can infer that there is a strong relationship between two numeric variables when the points on a scatterplot cluster tightly around a straight line. are randomly scattered in no clear pattern. display a positive relationship. display a negative relationship.

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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**Understanding Scatterplots: Identifying Strong Relationships**

When analyzing scatterplots, one can infer the presence of a strong relationship between two numeric variables if the data points exhibit specific patterns. Consider the following scenarios:

- **Cluster tightly around a straight line.**
  - This indicates a strong relationship, where the data points are consistently aligned.

- **Are randomly scattered in no clear pattern.**
  - This suggests a lack of relationship, as the data points do not follow any discernible trend.

- **Display a positive relationship.**
  - In this case, as one variable increases, the other also tends to increase, indicating a positive correlation.

- **Display a negative relationship.**
  - Here, as one variable increases, the other tends to decrease, indicating a negative correlation.

Understanding these patterns is crucial for interpreting the strength and direction of relationships in data analysis.
Transcribed Image Text:**Understanding Scatterplots: Identifying Strong Relationships** When analyzing scatterplots, one can infer the presence of a strong relationship between two numeric variables if the data points exhibit specific patterns. Consider the following scenarios: - **Cluster tightly around a straight line.** - This indicates a strong relationship, where the data points are consistently aligned. - **Are randomly scattered in no clear pattern.** - This suggests a lack of relationship, as the data points do not follow any discernible trend. - **Display a positive relationship.** - In this case, as one variable increases, the other also tends to increase, indicating a positive correlation. - **Display a negative relationship.** - Here, as one variable increases, the other tends to decrease, indicating a negative correlation. Understanding these patterns is crucial for interpreting the strength and direction of relationships in data analysis.
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