This document outlines the least squares method for finding the equation of a linear regression line that best fits a set of data points. It provides the mathematical formulas for calculating the slope (a) and y-intercept (b) of the line. As an example, it analyzes turnover data from 2007 to 2011 for a company to estimate turnover in 2012. The slope is calculated as 79.4 and the y-intercept as 1.8, providing the final estimated linear regression equation of y = 79.4x + 1.8 to predict a 2012 turnover of around 478,200 euros.