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13. Assumption SLR.4 (Zero Conditional Mean) One Crucial Assumption In The Simple Linear Regression Model Is That The Error Term U Has A Mean Of

13. Assumption SLR.4 (Zero Conditional Mean) One Crucial Assumption In The Simple Linear Regression Model Is That The Error Term U Has A Mean Of Zero, Conditional On The Value Of The Explanatory Variable R. Suppose You Are Using The Following Simple Linear Regression Model To Study The Effect Of Education On Salary. In This Case, Assume That Besides

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Drop down option #1: zero or nonzero / Drop down option #2: holds or does not hold


13. Assumption SLR.4 (Zero Conditional Mean) One crucial assumption in the simple linear regression model is that the error term has a mean of zero, conditional on the value of the explanatory variable I. Suppose you are using the following simple linear regression model to study the effect of education on salary. In this case, assume that besides education, natural ability level is the only other factor that influences salary, and therefore, u and ability level are equivalent. sal Bo+Bieduc+u where educ years of education sal = salary in tens of thousands of dollars u = the normalized value of ability relative to the average ability of all individuals in the population Note: A positive value for indicates higher than average ability, a negative value for indicates below average ability, and a value of 0 for indicates average ability If u has an expected value of 0, conditional on educ, then E (uleduc)=0, and therefore, E(sal|educ) = Though impossible in reality, suppose you have a scatter plot of the expected salary for each level of education in the population E(salleduc). These expected salaries are denoted by the blue dots on the following graph. Suppose you also have the line representing the population function when the zero conditional mean assumption holds, labeled as Bo+B educ and depicted as the black line on the graph. Refer to the graph and answer the question that follows.

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