Linear Models for DS

Catalog description

Linear Models for Data Science: Least squares theory and Gauss-Markov theorem, confidence intervals, significance tests and multiple comparison tests, multiple linear regression, simple, partial and multiple correlation, variable selection, model diagnostics, orthogonal polynomials, analysis of variance in fixed and random effects models, randomized blocks, bases and singular value decomposition.