This document discusses linear regression analysis. It defines the linear regression equation as Y = a + bX, or Y = β0 + β1X + ε, where Y is the dependent variable, X is the independent variable, β0 is the intercept, β1 is the slope, and ε is the error term. It provides formulas for estimating the slope and intercept using summation notation. It also explains how to interpret the regression results by decomposing the total sum of squares into the regression sum of squares and error sum of squares, with a better fit indicated by a larger ratio of SSR to SST and a smaller error sum of squares.