Karl Pearson’s Coefficient of Correlation, often simply referred to as Pearson’s correlation coefficient, is a measure of the linear relationship between two variables. It ranges from -1 to 1, where:

1 indicates a perfect positive linear relationship, -1 indicates a perfect negative linear relationship, 0 indicates no linear relationship. Using the actual mean method, we can simplify the calculations, specially when dealing with large datasets. Here’s a detailed breakdown of the process:

It concludes that The actual mean method simplifies calculations of Pearson’s correlation coefficient, making it easier to handle large datasets.