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.
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
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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
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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