STAT 230

Author

Paula Moraga

STAT 230 - Linear Models

Course overview

This course is an introduction to the formulation and use of linear models and generalizations including parameter estimation and inference for such models in a variety of settings. Emphasis will be split between understanding the theoretical foundations of the models and the ability to apply the models to answer scientific questions.

Statistical analyses will be conducted using R and the integrated development environment (IDE) RStudio.

Example: How does physical activity relate to body mass index (kg/m^2)?

Assignments

There will be homeworks that will be submitted to Blackboard by the due date. Late homeworks will not be accepted, unless prior arrangements have been made.

Exams

There will be one midterm exam to be scheduled inside of the regular class hours, and one comprehensive final exam to be scheduled by the registrar’s office.

No written material may be brought into the examination, except for one page (one side) of handwritten notes. A simple calculator may be used.

Example Midterm exam

Method of evaluation

50% - Final exam
25% - Midterm exam
25% - Homework

Required knowledge

Advanced and multivariate calculus, linear algebra, probability and statistics.

References

  1. Christensen (2011) Plane Answers to Complex Questions: the Theory of Linear Models, Springer
  2. Wood (2015) Core Statistics, Cambridge University Press
  3. Seber and Lee (2003) Linear Regression Analysis, Wiley
  4. Hocking (1996) Methods and Applications of Linear Models: Regression and the Analysis of Variance, Wiley
  5. McCullagh and Nelder (1989) Generalized Linear Models, Chapman & Hall/CRC
  6. Kariya and Kurata (2004) Generalized Least Squares, Wiley
  7. Hastie and Tibshirani (1990) Generalized Additive Models, Chapman & Hall/CRC
  8. Davison (2003) Statistical Models, Cambridge University Press
  9. Faraway (2005) Linear Models with R, Chapman & Hall/CRC
  10. Faraway (2006) Extending the Linear Model with R, Chapman & Hall/CRC
  11. Wood (2006) Generalized Additive Models: An Introduction with R (Chapman & Hall/CRC)
  12. Moore (2016) Applied Survival Analysis Using R. Springer

License

You may not copy or distribute the course materials.