The image shows a scatter plot where a series of data points are plotted on an XY axis. You are given options to select the range of correlation coefficients (r-values) based on the distribution of the points.

Looking at the scatter plot, there appears to be a general upward trend, where as $X$ increases, $Y$ tends to increase as well, although the points are somewhat spread out. This suggests a moderate positive correlation.

Based on the visual pattern of the scatter plot:

• The points do not follow a perfect linear trend, so the correlation is not close to +1.
• There is a clear upward trend, so it is not near zero.
• The points are somewhat spread out, so the correlation is likely not very high.

Given these factors, the best option would be +0.40 to +0.59 (Medium Positive).

Would you like a deeper explanation on correlation coefficients or how to calculate them from data?

Here are 5 related questions to expand on this topic:

1. How is the Pearson correlation coefficient calculated from raw data?
2. What are some real-life examples where medium positive correlation is observed?
3. How can you interpret different ranges of correlation values in practice?
4. What is the difference between positive and negative correlation?
5. How does the spread of data points affect the strength of correlation?

Tip: Always visualize the data first when analyzing correlations—it can give you quick insight into the relationship between variables!