Squaring the Pearson correlation coefficient (r²) tells us?

Squaring the Pearson correlation coefficient (r²) provides valuable insight into the relationship between two variables by quantifying how much of the total variance in one variable can be explained by the variance in the other variable. Specifically, r² expresses the proportion of variance that is shared between the two variables, effectively indicating the strength and clarity of the relationship.

For instance, if r² is 0.49, this means that 49% of the variance in one variable can be attributed to the variance in the other variable, suggesting a strong relationship. Conversely, an r² value of 0.01 would indicate that only 1% of the variance is shared, suggesting a weak relationship. It's crucial to recognize that this measure does not provide information on the direction of the relationship (whether positive or negative), nor does it imply statistical significance by itself. Thus, option B aptly captures the essence of what squaring the Pearson correlation coefficient reveals.