Economics 2182A/B Lecture Notes - Lecture 6: Simple Linear Regression, Regression Analysis, Dependent And Independent Variables
19 Nov 2018
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Announcements: assignment 1 will be posted this thursday. In a simple linear regression with one variable, the coefficient 1 indicates the base (eg. the base salary if you have no points per game). 1 represents the effect of having 100 points per game for example, holding all other variables constant. + b4sg + b5sf + b6pf: b3 is the difference between pg and c; b4 is the difference between sg and c, typically the variable we leave out is the one with the largest numbers. Omitted variable bias: an example: if we are interested in the salaries of workers and why some people earn higher wages and some earn lower wages. There could be many different reasons, one being years of education. If we run the regression on salary and regression and it turned out to be a positive number (statistically significant), we could conclude that higher education suggests higher salary.
