Final answer:
A near-zero coefficient of determination (r²) in the scatter plot for average monthly temperature and rate of precipitation in Belleview indicates no significant correlation between these two variables.
Step-by-step explanation:
If a scatter plot's coefficient of determination (r²) is very close to zero, it suggests that there is no correlation between the variables being studied. In the case of Belleview's average monthly temperature and rate of precipitation, a near-zero value of r² indicates that there is no significant linear relationship between these two variables. This means that knowing the average monthly temperature would not help to predict the average rate of precipitation, and vice versa. The correlation coefficient (r) is another measure to consider. If r² is close to zero, r would also indicate a weak to no correlation.
It is also crucial to view the scatter plot visually to discern any possible patterns. Even if the correlation coefficient is significant, if the scatter plot indicates that a line isn't the best fit (e.g., if the data points suggest a curve), then a linear model may not be appropriate. In the Belleview example, however, the question explicitly states that r² is nearly zero, reinforcing the idea that there is no correlation between temperature and precipitation.