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Archived Curricula Guide 2011–2012
Curricula Guide is archieved. Please refer to current Curricula Guides
TILTA6 Regression Analysis 8 ECTS

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.


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


Modes of study

An assignment which must be completed before the last interim (or final) test.


Numeric 1-5.

Recommended year of study

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

Study materials

  1. Chatterjee, S., Hadi, A. S., Regression analysis by example, 4th ed. Wiley 2006.
  2. Cook, R. D., Regression graphics: ideas for studying regressions through graphics. Wiley 1998.
  3. Cook, R. D., Weisberg, S., Applied regression including computing and graphics. Wiley 1999.
  4. Draper, N. R., Smith, H., Applied regression analysis, 3rd ed. Wiley 1998.
  5. 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.
  6. Neter, J., Kutner, M. H., Nachtsheim, C. J., Wasserman, W., Applied linear statistical models, 4th ed. McGraw-Hill/Irwin 1996.
  7. Puntanen, S., Regressioanalyysi I-II. B48-49/MTF, University of Tampere 1999.
  8. Ryan, T. P., Modern regression methods, 2nd ed. Wiley 2009.
  9. Seber, G. A. F., Lee, A. J., Linear regression analysis, 2nd ed. Wiley 2003.
  10. Weisberg, S., Applied linear regression, 3rd ed. Wiley 2005.

Belongs to following study modules

School of Information Sciences
Archived Teaching Schedule. Please refer to current Teaching Shedule.
School of Information Sciences