what does the relationship mean with two things in scatter plots?
In scatter plots, the relationship between two variables is visualized by plotting their values on a two-dimensional coordinate system. The position of each point represents the values of the two variables for each data observation.
The relationship between the two variables in a scatter plot can provide information about their possible association or correlation. Here are some common types of relationships observed in scatter plots:
1. Positive Relationship: Points in the plot roughly follow an upward trend or form a pattern that slopes upward. This indicates that as one variable increases, the other variable tends to increase as well.
2. Negative Relationship: Points in the plot roughly follow a downward trend or form a pattern that slopes downward. This indicates that as one variable increases, the other variable tends to decrease.
3. No Relationship: Points are scattered randomly across the plot, showing no clear trend or pattern. This suggests that there is no evident association between the two variables.
4. Linear Relationship: Points in the plot form a straight line or approximate a straight line. This indicates a strong and consistent relationship between the two variables, implying that a change in one variable is directly proportional to a change in the other variable.
5. Non-linear Relationship: Points in the plot form a curved or non-linear pattern. This implies that the variables exhibit a more complex relationship, where the rate of change may vary as the values of the variables change.
It's important to note that scatter plots depict relationships and correlations, but they do not establish causality. Further statistical analysis, such as regression, is needed to determine the strength and significance of the relationship and make any causal inferences.