Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

401-0649-00L  Applied Statistical Regression

SemesterAutumn Semester 2016
LecturersM. Dettling
Periodicityyearly recurring course
Language of instructionEnglish



Catalogue data

AbstractThis course offers a practically oriented introduction into regression modeling methods. The basic concepts and some mathematical background are included, with the emphasis lying in learning "good practice" that can be applied in every student's own projects and daily work life. A special focus will be laid in the use of the statistical software package R for regression analysis.
ObjectiveThe students acquire advanced practical skills in linear regression analysis and are also familiar with its extensions to generalized linear modeling.
ContentThe course starts with the basics of linear modeling, and then proceeds to parameter estimation, tests, confidence intervals, residual analysis, model choice, and prediction. More rarely touched but practically relevant topics that will be covered include variable transformations, multicollinearity problems and model interpretation, as well as general modeling strategies.

The last third of the course is dedicated to an introduction to generalized linear models: this includes the generalized additive model, logistic regression for binary response variables, binomial regression for grouped data and poisson regression for count data.
Lecture notesA script will be available.
LiteratureFaraway (2005): Linear Models with R
Faraway (2006): Extending the Linear Model with R
Draper & Smith (1998): Applied Regression Analysis
Fox (2008): Applied Regression Analysis and GLMs
Montgomery et al. (2006): Introduction to Linear Regression Analysis
Prerequisites / NoticeThe exercises, but also the classes will be based on procedures from the freely available, open-source statistical software package R, for which an introduction will be held.

In the Mathematics Bachelor and Master programmes, the two course units 401-0649-00L "Applied Statistical Regression" and 401-3622-00L "Regression" are mutually exclusive. Registration for the examination of one of these two course units is only allowed if you have not registered for the examination of the other course unit.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits5 credits
ExaminersM. Dettling
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 120 minutes
Additional information on mode of examinationExam questions may be answered in English or in German.

Mathematics Bachelor / Mathematics Master: see notice in the catalogue data.
Written aidsOpen book, i.e. any written material is allowed. We recommend to bring a pocket calculator.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

 
Main linkCourse Webpage
Only public learning materials are listed.

Courses

NumberTitleHoursLecturers
401-0649-00 VApplied Statistical Regression2 hrs
Mon08-10HG E 1.2 »
M. Dettling
401-0649-00 UApplied Statistical Regression
Mon 10-12 might not work for all different programmes where this course is offered. On sufficient demand, other slots (tentatively Mon 15-17 or Fri 10-12) for the exercise sessions can be offered.
1 hrs
Mon/2w10-12HG D 7.2 »
M. Dettling

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

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