Answer :
To match correlation patterns with scatter plot descriptions, it's important to understand how different correlations appear on a scatter plot. Let's break down each option:
A. High Positive: This correlation means that as one variable increases, the other variable tends to also increase in a strong, linear manner.
- Associated Description: 2. A pattern ascending from left to right with the variables moving in the same direction.
B. High Negative: This correlation means that as one variable increases, the other variable tends to decrease in a strong, linear manner.
- Associated Description: 5. A scatter diagram with a line descending from left to right with the variables moving in opposite directions.
C. Low Correlation: Here, there is a weak relationship between the variables. Points are spread out around a line, with no clear pattern.
- Associated Description: 1. A scatter diagram with widely scattered data points above and below an upward trending best-fit line.
D. No Correlation: There is no discernible pattern or relationship between the variables. The points are randomly scattered.
- Associated Description: 3. A scatter diagram with scattered data points that don't form any particular line.
E. Nonlinear: This means the relationship between the variables isn't a straight line. The data might form a curve or change direction at a certain point.
- Associated Description: 4. A scatter diagram with a significant change in the dependent variable taking place at a certain value of the independent variable.
Understanding these correlations helps in analyzing data patterns and predicting variable relationships.
