Assumptions Required for OLS to be Unbiased Assumption M1: The model is linear in the parameters Assumption M2: The data are collected through independent, random sampling Assumption M3: The data are not perfectly multicollinear. Assumption M4: The error term has zero mean Assumption M5: The error term is uncorrelated with each independent variable and all functions of each independent variable. Additional Assumption Required for OLS to be BLUE Assumption M6: The error term has constant variance. Note that these assumptions are theoretical and typically can’t be proven or disproven.

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