About this document
Assumptions of Multiple Linear Regression by Adrian Alexander is a document available to read on EtoBox.
1) The document discusses the asymptotic properties of ordinary least squares (OLS) regression as the sample size increases. 2) It shows that under certain assumptions, including no correlation between regressors and errors, the OLS estimator remains consistent and asymptotically normal even if the errors are not normally distributed. 3) This means that hypothesis tests using the OLS estimators, such as the t-test and F-test, will be approximately valid for large samples sizes even if the error distribut
- Author
- Adrian Alexander
- Language
- EN