Which of the following statements is FALSE?

The statement regarding R values being derivable directly from Chi-square without access to the raw data is considered false. R values, or correlation coefficients, reflect the strength and direction of a linear relationship between two variables. To calculate an R value accurately, one typically requires access to the raw data to determine the degree of association between those variables.

In contrast, the Chi-square statistic is used for hypothesis testing, particularly in categorical data analysis. While there is a relationship between Chi-square and R values in the context of contingency tables, the conversion from Chi-square to R requires the raw frequency counts and the observed versus expected values, rather than being a direct derivation. This makes it essential to have access to the raw data to compute R values.

The other statements surrounding significant R and Chi-square values increasing with sample size (N) are generally true. As N increases, the power of a statistical test also increases, leading to greater chances of detecting a significant relationship when there is one, which translates to higher R and Chi-square values. Additionally, Chi-square statistics can indeed cover a wider numerical range compared to correlation coefficients, which are bound between -1 and 1. Thus, the understanding of the relationship between these statistical measures is critical in interpreting result validity in