401-0649-00L Applied Statistical Regression
| Semester | Autumn Semester 2020 |
| Lecturers | M. Dettling |
| Periodicity | yearly recurring course |
| Language of instruction | English |
Courses
| Number | Title | Hours | Lecturers | ||||
|---|---|---|---|---|---|---|---|
| 401-0649-00 V | Applied Statistical Regression The lecturers will communicate the exact lesson times of ONLINE courses. | 2 hrs |
| M. Dettling | |||
| 401-0649-00 U | Applied 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. The lecturers will communicate the exact lesson times of ONLINE courses. | 1 hrs |
| M. Dettling |
Catalogue data
| Abstract | This 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. |
| Learning objective | The students acquire advanced practical skills in linear regression analysis and are also familiar with its extensions to generalized linear modeling. |
| Content | The 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 notes | A script will be available. |
| Literature | Faraway (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 / Notice | The 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 "Statistical Modelling" 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 credits | 5 credits |
| Examiners | M. Dettling |
| Type | session examination |
| Language of examination | English |
| Repetition | The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit. |
| Mode of examination | written 120 minutes |
| Additional information on mode of examination | Exam questions may be answered in English or in German. Mathematics Bachelor / Mathematics Master: see notice in the catalogue data. |
| Written aids | Open 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
| No public learning materials available. | |
| Only public learning materials are listed. |
Groups
| No information on groups available. |
Restrictions
| There are no additional restrictions for the registration. |
