When calculating Pearson's correlation (r), what is considered a strong value?

Pearson's correlation coefficient (r) ranges from -1 to 1, with values closer to 1 or -1 indicating a stronger linear relationship between two variables. A strong correlation is typically considered to be a value greater than 0.7 (or less than -0.7).

In this context, a value of 0.8 signifies a strong positive relationship, meaning that as one variable increases, the other variable also tends to increase significantly. This high value close to 1 suggests that the two variables are closely related in a linear fashion, reflecting a reliable connection that can be useful in predictive analytics and understanding relationships in data.

Values like 0.3 or 0.5 suggest weaker correlations, indicating a less pronounced relationship where changes in one variable do not strongly predict changes in the other. A choice of 1.5 is not applicable since Pearson's r cannot exceed 1, making it invalid in the context of correlation coefficients. Thus, the correct answer highlights an understanding of strong correlations in data analytics.