If a scatter plot shows points that are closely clustered together, what can you infer about the correlation between the variables?

If a scatter plot shows points that are closely clustered together, you can infer that there is a strong correlation between the variables. The degree of clustering indicates how closely the values of one variable are related to the values of the other variable. Here are some key points to consider: 1. **Positive Correlation**: If the points cluster in a way that, as one variable increases, the other variable also increases, this indicates a strong positive correlation. 2. **Negative Correlation**: Conversely, if the points cluster such that as one variable increases, the other variable decreases, this indicates a strong negative correlation. 3. **Strength of Correlation**: The closer the points are to forming a straight line (either upward or downward), the stronger the correlation. If the points are widely scattered, the correlation is weak. 4. **No Correlation**: If the points are randomly scattered with no discernible pattern, this suggests that there is little to no correlation between the variables. In summary, closely clustered points in a scatter plot suggest a strong correlation, either positive or negative, depending on the direction of the clustering.