The correlation coefficient is often used and more often misused as a universal parameter expressing the quality in linear regression analysis. The popularity of this dimensionless quantity is evident as it is easy to communicate and considered to be unproblematic to comprehend. However, illustrative examples will demonstrate that the correlation coefficient is highly ineffective as a stand-alone quantity without reference to the number of observations, the pattern of the data and the slope of the regression line. Much more efficient quality methodologies are available where the correct technique depends on the purpose of the investigation. These relevant and precise methods in quality assurance of linear regression as alternative to the correlation coefficient are presented.