1. How to detect non-linearity, normality, non-constant variance or whether explanatory variables are correlated with the error term? 2. When the sum of the errors ≠ 0, what are the main causes? Should you first investigate this problem in order to fix the model? 3. What to do to fix/adjust the model if one or all of the classical assumptions cited above were violated? 4. What are the consequences for the model ? Are the estimators still be unbiased? (by the way, what is an unbiased estimator?) What happens with the t-test? Can you rely on the results?
- How to detect non-linearity, normality, non-constant variance or whether explanatory variables are correlated with the error term?
- When the sum of the errors ≠ 0, what are the main causes? Should you first investigate this problem in order to fix the model?
- What to do to fix/adjust the model if one or all of the classical assumptions cited above were violated?
- What are the consequences for the model ? Are the estimators still be unbiased? (by the way, what is an unbiased estimator?) What happens with the t-test? Can you rely on the results?
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