[Slides 112-138] The Linear Model in an inferential context: introduction, additional assumptions, the model in a multiple linear regression context. The matrix/vector notation for the Model: the Model equation and the random vector of estimators of the model parameters (beta-hat). Tools to work with random vectors: the expected vector and its properties; the matrix of (co-)variances and its properties; the MultiNormal distribution and its properties; the Linear Model in matrix/vector notation. First consequences of the model: the distribution of the random vector Y of response variable observations; the distribution of the vector of estimators beta-hat (with proofs and interpretations).

Nota: Esta aula foi leccionada na quarta-feira, dia 30.3.22, das 15h às 17h35, na Sala S3, simultaneamente presencial e por zoom.