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
Modes of study
An assignment which must be completed before the last interim (or final) test.
Evaluation
Numeric 1-5.
Recommended year of study
2. year autumn
2. year spring
3. year autumn
3. year spring
Study materials
Chatterjee, S., Hadi, A. S., Regression analysis by example, 4th ed. Wiley 2006.
Cook, R. D., Regression graphics: ideas for studying regressions through graphics. Wiley 1998.
Cook, R. D., Weisberg, S., Applied regression including computing and graphics. Wiley 1999.
Draper, N. R., Smith, H., Applied regression analysis, 3rd ed. Wiley 1998.
Isotalo, J., Puntanen, S., Styan, G. P. H., Formulas useful for linear regression analysis and related matrix theory, 4th ed. A384/MTL, University of Tampere 2008.
Neter, J., Kutner, M. H., Nachtsheim, C. J., Wasserman, W., Applied linear statistical models, 4th ed. McGraw-Hill/Irwin 1996.
Puntanen, S., Regressioanalyysi I-II. B48-49/MTF, University of Tampere 1999.
Ryan, T. P., Modern regression methods, 2nd ed. Wiley 2009.
Seber, G. A. F., Lee, A. J., Linear regression analysis, 2nd ed. Wiley 2003.
Weisberg, S., Applied linear regression, 3rd ed. Wiley 2005.