Applied Linear Models (8 ECTS)

Course Code: 
Elective Courses

Normal linear model through matrices. Statistical inference, LRT, general linear hypothesis. Quadratic forms and distributions, independence between quadratic forms. Weighted regression, variance modeling. Sensitivity analysis. Basic principles of design of experiments. Factorial experiments with one factor. Sum-to-zero, corner point parameterization, estimated parameters, model ANOVA. Contrasts and multiple comparisons. Two factors, interaction, estimated parameters, model ANOVA. Multiple comparisons in factorial experiments. The case of more than two factors. Blocking in factorial experiments. Incomplete blocks experiments. Blocking and confounding. Fractional factorial experiments. Random effects models, split-plot experiments.

Recommended Reading

  • Chatterjee, S. and Hadi, A.S. (2012). Regression analysis by example, Wiley.
  • Draper N.R. and Smith, H. (1997). Εφαρμοσμένη Ανάλυση Παλινδρόμησης, Παπαζήσης
  • Montgomery, D.C., Peck, E.A. and Vining, G.G. (2012). Introduction to Linear Regression Analysis, Wiley.
  • Montgomery, D.C. (2012). Design and analysis of experiments, Wiley.
  • Ryan, T.P. (2008). Modern regression methods, Wiley.
  • Weisberg, S. (2014). Applied Linear Regression, Wiley