# Basic course on regression modelling (5 ECTS)

This intensive course starts with a short overview of the principles of statistical analysis. It
does not replace an elementary course in statistics but helps by examples to understand how
relationships between phenomena can be investigated and their significance assessed by
simple statistical models. The course is especially intended to those wishing to improve their
understanding of statistical inference and modelling.

#### TOPICS OF THE COURSE

• Basic principles of statistical modelling
• The linear regression model: univariate and multivariate setting
• How to interpret the results of a regression model: what is a good model?
• How to assess the uncertainty and assumptions of the model?
• The logistic regression model: univariate and multivariate setting
• How to interpret the results of a logistic regression model?
• How to assess the goodness-of-fit of a logistic model?

#### TIMETABLE

• Thursday 24.09.2015; 10:00 – 14:00, Calonia, Cal3
• Friday 25.09.2015; 10:00 – 12:00, Educarium, Edu2; 12:00 – 14:00, Aud. Edu1
• Thursday 01.10.2015; 10:00 – 14:00, Educarium, Edu2
• Practicals on each day 14-16, computer class

#### TEACHING METHODS AND EVALUATION

• Lectures and group assignments (12 h)
• Computer practicals (6 h)
• Independent/group work (pass/fail)

#### TEACHERS

• Lectures: Prof. Mervi Eerola (UTU Center of Statistics)
• Practicals and group assignments: Lecturers Jouko Katajisto and Henri Nyberg

#### LEARNING OUTCOMES

By the end of the course the student should be able to
• understand the basic principles of statistical modelling;
• recognize the most common regression models and can choose a plausible statistical model for his or her own problem;
• evaluate critically the modelling results and their sensitivity to model assumptions

#### REGISTRATION:

NettiOpsu or Eila Seppänen (eila.seppanen@utu.fi)

# Basic course on regression modelling (5 ECTS)

This intensive course starts with a short overview of the principles of statistical analysis. It does not replace an elementary course in statistics but helps by examples to understand how relationships between phenomena can be investigated and their significance assessed by simple statistical models. The course is especially intended to those wishing to improve their understanding of statistical inference and modelling.

#### TOPICS OF THE COURSE

• Basic principles of statistical modelling
• The linear regression model: univariate and multivariate setting
• How to interpret the results of a regression model: what is a good model?
• How to assess the uncertainty and assumptions of the model?
• The logistic regression model: univariate and multivariate setting
• How to interpret the results of a logistic regression model?
• How to assess the goodness-of-fit of a logistic model?

#### TIMETABLE

• Thursday 24.09.2015; 10:00 – 14:00, Calonia, Cal3
• Friday 25.09.2015; 10:00 – 12:00, Educarium, Edu2; 12:00 – 14:00, Aud. Edu1
• Thursday 01.10.2015; 10:00 – 14:00, Educarium, Edu2
• Practicals on each day 14-16, computer class

#### TEACHING METHODS AND EVALUATION

• Lectures and group assignments (12 h)
• Computer practicals (6 h)
• Independent/group work (pass/fail)

#### TEACHERS

• Lectures: Prof. Mervi Eerola (UTU Center of Statistics)
• Practicals and group assignments: Lecturers Jouko Katajisto and Henri Nyberg

#### LEARNING OUTCOMES

By the end of the course the student should be able to
• understand the basic principles of statistical modelling;
• recognize the most common regression models and can choose a plausible statistical model for his or her own problem;
• evaluate critically the modelling results and their sensitivity to model assumptions

#### REGISTRATION:

NettiOpsu or Eila Seppänen (eila.seppanen@utu.fi)