The Pearson Correlation Coefficient, Explained Simply

The Pearson correlation coefficient is explained as a statistical measure to quantify the linear relationship between two continuous variables. It is presented as a crucial step before applying a linear regression model, using a dataset of salary versus years of experience as a practical example. The content provides a detailed, step-by-step mathematical walkthrough of the calculation, covering mean, variance, standard deviation, and covariance. This process demonstrates how covariance is normalized to produce a unitless coefficient between -1 and +1, which indicates the strength and direction of the linear association.