The total sum of squares and the total degrees of freedoms are disaggregated by calculating in sample variance and "between" sample variance and their respective degrees of freedoms. It is demonstrated numerically that both these measures add up to the total sum of squares and the total degrees of freedom.
First some terminology is explained. Then the interpretations of the coefficients and constants of the function are discussed. Afterwards the zero conditional mean assumption regarding the residual is problematized. Lastly, a graphical representation of a regression line is given and the least sum of squared errors is introduced and the equation for the coefficient of the linear function as well as for the intercept is given.
Economists like to base their theories on individual decision making. Individuals, the idea goes, have their own interests and preferences, and if we don’t include these in our theory we can’t be sure how people will react to changes in their economic circumstances and policy. While there may be social influences, in an important sense the buck stops with individuals. Understanding how individuals process information to come to decisions about their health, wealth and happiness is crucial. You can count me as someone who thinks that on the whole, this is quite a sensible view.