Chapter 5: Matrix Approaches to Simple Linear Regression
Chapter 5: Matrix Approaches to Simple Linear Regression
Chapter 5: Matrix Approaches to Simple Linear Regression
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Vec<strong>to</strong>rsOverview<strong>Matrix</strong> Algebra➤ Introduction➤ Definitions➤ Matrices➤ <strong>Matrix</strong> Computing➤ MatricesAlgebraMore MatricesGeneral <strong>Linear</strong>ModelOther <strong>Matrix</strong>ProductsWrapping Up● A vec<strong>to</strong>r is a matrix where one dimension is equal <strong>to</strong> sizeone.✦ Column vec<strong>to</strong>r: A column vec<strong>to</strong>r is a matrix of size r × 1.✦ Row vec<strong>to</strong>r: A row vec<strong>to</strong>r is a matrix of size 1 × c.● Vec<strong>to</strong>rs allow for geometric representations of matrices.● The Pearson correlation coefficient is a function of the anglebetween vec<strong>to</strong>rs.● Much of the statistical theory given in this course (andANOVA-type courses) can be conceptualized by projectionsof vec<strong>to</strong>rs (think of the dependent variable Y as a columnvec<strong>to</strong>r).Lecture 17 Psychology 790
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