Which one of the following statements about the Pearson correlation coefficient is FALSE?

The Pearson correlation coefficient is a statistical measure that assesses the strength and direction of the relationship between two continuous variables. The correct answer highlights a key limitation of this measure: while the coefficient can tell us about the degree of correlation, it does not imply a causal relationship between the two variables.

The correlation coefficient ranges from -1 to +1, where a value of +1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship, and 0 indicates no linear relationship. Additionally, a positive correlation signifies that as one variable increases, the other variable tends to also increase, while a negative correlation indicates that as one variable increases, the other tends to decrease. However, correlation does not imply causation; just because two variables are correlated does not mean that one variable directly influences or causes changes in the other.

Understanding this distinction is crucial in research and data analysis, as it prevents misinterpretation of correlational data as indicative of causal relationships. Thus, the assertion that the Pearson correlation coefficient can provide information about cause and effect is indeed misleading and incorrect.