Applied linear modelling emphasizing data analysis using software including statistical inference review, visualization, multiple regression, logistic regression, and extensions. Core topics include assumptions, estimation, confidence/prediction intervals, hypothesis testing, diagnostics, indicator variables, cross validation, prediction, model building and model assessment. Other topics may include random effects or smoothing methods.
Applied linear modelling emphasizing data analysis using software including statistical inference review, visualization, multiple regression, logistic regression, and extensions. Core topics include assumptions, estimation, confidence/prediction intervals, hypothesis testing, diagnostics, indicator variables, cross validation, prediction, model building and model assessment. Other topics may include random effects or smoothing methods.
