General description

The course familiarises students with the structure of regression models and teaches them to apply them (and the analysis of variance).

Learning outcomes

See content.

Contents

The topics covered by the course include univariate regression analysis, the definition of a linear model, parameter estimation, hypothesis testing, a model for the analysis of variance and special regression models as well as problems associated with constructing a regression model. The course includes an assignment which must be completed before the last interim (or final) test.

Teaching language

Finnish

Evaluation

Numeric 1-5.

Recommended year of study

2. year autumn
2. year spring
3. year autumn
3. year spring

Study materials

1. Cook, R. D., Weisberg, S., Applied Regression Including Computing and Graphics. Wiley 1999.
2. Isotalo, J., Puntanen, S., Styan, G. P. H., Formulas Useful for Linear Regression Analysis and Related Matrix Theory. A350/MTF, Tampereen yliopisto 2005.
3. Neter, J., Kutner, M. H., Nachtsheim, C. J., Wasserman, W., Applied Linear Statistical Models, 4th ed. McGraw-Hill/Irwin 1996.
4. Puntanen, S., Regressioanalyysi I-II. B48-49/MTF, Tampereen yliopisto 1999.
5. Weisberg, S., Applied Linear Regression, 3rd ed. Wiley 2005.
6. Cook, R. D., Regression Graphics: Ideas for Studying Regressions through Graphics. Wiley 1998.
7. Seber, G. A. F., Lee, A. J., Linear Regression Analysis. Wiley 2003.
8. Chatterjee, S., Hadi, A. S., Price, B., Regression Analysis by Example, 3rd ed. Wiley 2000.
9. Draper, N. R., Smith, H., Applied Regression Analysis, 3rd ed. Wiley 1998.

Belongs to following study modules