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This lecture focuses on the fundamentals of bivariate statistics, particularly classical regression analysis. It outlines the division of data variation, error definitions, and the principles of classical linear regression. A step-by-step derivation of the least squares method is presented, supplemented by examples and significance testing methods, including ANOVA. The lecture also addresses common warnings and provides resources for further understanding, including a link to matrix inverses. Ideal for students and professionals seeking to enhance their knowledge in regression analysis.
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Example Satisfied? Not really. Let’s derive!
Deriving Least Squares, 4 Need a refresher? http://mathworld.wolfram.com/MatrixInverse.html