This is a good explanation of the assumptions for linear regression. Unfortunately, it does not differentiate between the ones orinignating from the use of the OLS model.
These 5 assumptions are conditions for the OLS to be BLUE (the best, linear, unbiased estimator), with the unbiasedness (E(β1^)=β1 being the 6th condition/assumption. Actually it is the 1st assumption by order.
This is a good explanation of the assumptions for linear regression. Unfortunately, it does not differentiate between the ones orinignating from the use of the OLS model.
This is wrong, only assumption 1-4 have to be satisfied to have unbiasedness, Heteroskedasticity has no effect on the unbiasedness of the estimators
These 5 assumptions are conditions for the OLS to be BLUE (the best, linear, unbiased estimator), with the unbiasedness (E(β1^)=β1 being the 6th condition/assumption. Actually it is the 1st assumption by order.
Formal Tests: White's Test, Durban-Watson Test, Ramsay-Reset Test, Variation Inflation Test.
Very helpful! Thank you!
This was helpful... Thanks
chigirl 16 how r u?
Great video
Easy and simple
thank yous that's help
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