course-details-portlet

ST2304 - Statistical Modelling for Biologists/Biotechnologists

About

Examination arrangement

Examination arrangement: Home exam
Grade: Letters

Evaluation Weighting Duration Grade deviation Examination aids
Home exam 100/100 4 hours

Course content

Practical use of the software package R. Multiple regression. Analysis of variance. Analysis of categorical data. Generalised linear models. Basic principles for statistical inference. Simulation from a model. Properties of estimators. Statistical power. Numerical maximisation of the likelihood function. Some asymptotic results. Model selection. Non-parametric tests.

Learning outcome

1. Knowledge. The student has an overview over the underlying assumptions and practical applications of multiple regression, analysis of variance, analysis of categorical data and generalised linear models using the software package R. In addition, the student knows how simulation methods can be used in finding properties of estimators, in hypothesis testing and in computation of power. The student also has basic knowledge about numerical methods for fitting non-standard models using maximum likelihood and how results from asymptotic theory can be used in estimating uncertainty in parameter estimates and in hypothesis testing. 2. Skills. The student can handle and analyse collected datasets using the software package R. The student is also capable of formulating simple, non-standard statistical models, implementing the model in computer code and fitting such models using standard numerical optimisation algorithms. In both situations, the student is able to assess the properties of a given method using simulations or using methods based on asymptotic theory.

Learning methods and activities

Lectures and compulsory computer exercises. Written final examination is the basis for the

grade awarded in the course. The re-sit examination may be given as an oral examination.

The lectures may be given in English. If the course is taught in English, the exam may be given only in English. Students are free to choose Norwegian or English for written assessments.

Compulsory assignments

  • Exercises

Further on evaluation

In the case that the student receives an F/Fail as a final grade after both ordinary and re-sit exam, then the student must retake the course in its entirety. Submitted work that counts towards the final grade will also have to be retaken. For more information about grading and evaluation, see «Teaching methods and activities».

Specific conditions

Compulsory activities from previous semester may be approved by the department.

Course materials

Will be announced at the start of the course.

Credit reductions

Course code Reduction From To
ST0201 7.5 AUTUMN 2010
TMA4255 7.5 AUTUMN 2010
Facts

Version: 1
Credits:  7.5 SP
Study level: Third-year courses, level III

Coursework

Term no.: 1
Teaching semester:  SPRING 2022

Language of instruction: English, Norwegian

Location: Trondheim

Subject area(s)
  • Statistics
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Mathematical Sciences

Examination

Examination arrangement: Home exam

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD Home exam (1) 100/100

Release
2022-06-01

Submission
2022-06-01


09:00


13:00

INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
  • 1) Merk at eksamensform er endret som et smittevernstiltak i den pågående koronasituasjonen.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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