Kursussøgning, efter- og videreuddannelse – Københavns Universitet

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Kursussøgning, efter- og videreuddannelse

Regression (Reg)

Practical information
Study year 2016/2017
Time
Block 3
Programme level Full Degree Master
ECTS 7,5 ECTS
Course responsible
  • Susanne Ditlevsen (7-75777563707067426f63766a306d7730666d)
  • Department of Mathematical Sciences
Course number: NMAK11022U

Course content

  • Multiple linear regression and least squares methods.
  • Generalized linear models.
  • Survival regression models.
  • Nonlinear effects and basis expansions.
  • Parametric, semiparametric and nonparametric likelihood methods. 
  • Aspects of practical regression analysis in R.

Learning outcome

Knowledge:

  • Linear, generalized linear and survival regression models.
  • Exponential dispersion models.
  • Likelihood, quasi-likelihood, nonparametric likelihood and partial likelihood methods.
  • R.


Skills: Ability to

  • perform a mathematical analysis of likelihood functions in a regression modeling context. 
  • compute parameter estimates for a regression model.
  • perform model diagnostics, statistical tests, model selection and model assessment for regression models.
  • construct confidence intervals for a univariate parameter of interest in theory as well as in practice.
  • use R to be able to work with the above points for practical data analysis.


Competences: Ability to

  • construct regression models using combinations of linear predictors, basis expansions, link-functions and variance functions.
  • interpret a regression model and predictions based on a regression model.
  • evaluate if a regression model is adequate. 

 

 

Recommended prerequisites

Statistik 2 (Stat2)

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Education

MSc Programme in Statistics
MSc Programme in Mathematics-Economy

Studyboard

Study Board of Mathematics and Computer Science

Course type

Single subject courses (day)

Duration

1 block

Schedulegroup

B
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Teaching and learning methods

5 hours of lectures for 7 weeks.
2 hours of exercises for 7 weeks.

Capacity

No limit

Language

English

Workload

Category Hours
Lectures 35
Theory exercises 14
Project work 39
Preparation 91
Exam 27
English 206

Exam

Type of assessment

Written assignment, 27 hours
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Aid

All aids allowed

Marking scale

7-point grading scale

Criteria for exam assessment

The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.

Censorship form

No external censorship
One internal examiner.

Re-exam

25 min. oral exam with 50 min. preparation time and several internal examiners. All aids allowed during preparation time, but only computer allowed during the examination.

If the compulsory practical group project was not approved during the course it must be handed in no later than two weeks before the beginning of the reexamination week. It has to be approved before the reexamination.

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