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we talked about omitted variable bias in in lecture two but this will be a slight repetition and and how it deals with internal validity okay so what if you have a a model and you leave out a a an x variable which is correlated with with one of the the included x variables and it the the omitted variable has an effect on on y itself then you are suffering from a method of variable bias and your your better estimate will will be biased so for example we we have the true population regression model and this model has two x variables uh explaining the variation in the y variable and we have here that the the expected value of of of the residual is zero no matter which level of the x variables we are looking at so what if we we omit the the uh x2 variable from the regression right and uh instead we we estimate uh y on on uh on just x one so in the in this regression we see that in that the the residual contains not only the the the the uh the w the the unbiased uh unbiased residual or unbi