In statistics, the Pearson correlation coefficient (PCC) [a] is a correlation coefficient that measures linear correlation between two sets of data. Karl Pearson’s coefficient of correlation (commonly denoted as r) is the most widely used method to quantify the linear relationship between two continuous variables. It provides a numerical value ranging from -1 to +1, indicating the direction and strength of the correlation. The formula for Karl Pearson’s correlation coefficient is: Rank Coefficient and Karl Pearson's Coefficient of Correlation: In engineering mathematics, coefficients of correlation are statistical measures that quantify the degree and direction of the relationship between two variables. They are used to determine how one variable may predict or relate to another, which is crucial in various engineering applications such as quality control, signal processing, and system optimization. 7.4 LET US SUM UP In the present unit, we mainly discussed about the two methods of computing coefficient of correlation. The first method is Pearson’s product moment correlation and the other is Spearman’s rank order correlation. Pearson’s product moment correlation is one of the methods to compute coefficient of correlation. This is mainly used when the assumptions of parametric statistics are met. This method is named after Karl Pearson, who invented this method. It is denoted by ...
