BIOS4000 – Design and analysis of biological studies

Schedule, syllabus and examination date

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Changes in the course due to coronavirus

Autumn 2020 the exams of most courses at the MN Faculty will be conducted as digital home exams or oral exams, using the normal grading scale. The semester page for your course will be updated with any changes in the form of examination.

See general guidelines for examination at the MN Faculty autumn 2020.

Course content

This course is a thorough introduction to design of biological studies and statistical analysis in biology. The focus is on the use of statistical models for analyzing biological patterns and processes. Students are taught fundamental skills in modern biological research through project work, exercises and computer exercises. The statistical environment R is used throughout the course.

Learning outcome

After completing this course, you are expected to:

  • Understand the difference between observational studies and experiments, and be able to assess the results from different types of studies in a biological context
  • Understand the importance of the terms pseudoreplication, confounding effects, experimental control, randomization, sampling skewness, stratified sampling and blocking in analysis of biological studies
  • Be able to carry out Monte Carlo simulations to assess different study design and statistical models
  • Be able to fit biologically relevant models based on the normal, binomial, and Poisson distributions (GLM), and calculate linear contrasts and predictions with confidence intervals, as well as evaluate how well these models fit the data (goodness of fit).
  • Know how to fit hierarchical models with normally distributed response variables and interpret these
  • Know how to assess the sources of bias in models fitted to biological data, including the effects of sampling skewness, measurement error in the predictive variables (attenuation) and loss of study units during the course of the study.
  • Be able to comprehend literature based on the contents of the course and be able to present this as a lecture for fellow students.

Formal prerequisite knowledge

STK1000 – Introduction to Applied Statistics or equivalent.

A background in elementary programming equivalent to the content of BIOS1100 – Introduction to computational models for Biosciences is strongly recommended.

Other recommended background courses are

BIOS1110 – Celle- og molekylærbiologi (Molecular and Cell biology)

BIOS1120 – Fysiologi (Physiology)

BIOS1140 – Evolusjon og genetikk (Evolution and genetics)

BIOS2100 – General Ecology

Overlapping courses

Teaching

The course includes lectures, tutorials, compulsory exercises with hand-in reports, and a compulsory literature review project resulting in a lecture a short lecture for fellow students (individually or in groups of two). The first lecture is compulsory. All written material is in English, and reports should be written in English. 

Attendance to the first lecture is mandatory, also for those on the waiting list. If you are unable to attend the first lecture you will lose your seat on the course if you do not inform the student administration studieinfo@ibv.uio.no prior to the first lecture.

Approved mandatory course work is valid for 3 years.

Examination

A final written exam (4 hours) counting 100% of the mark.

Mandatory course work must be approved before the student can attend the exam. Approved mandatory course work is valid for 3 years.

 

Withdrawal from an examination

It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt. It will also be counted as one of the three attempts to sit the exam for this course, if you sit the exam for one of the following courses: BIOS3000 – Design and analysis of biological studies, BIO2150 – Biostatistics and Study Design (discontinued), BIO2130 – Bio statistics (discontinued), BIO2110 – Experimental ecology (discontinued)

Examination support material

Examination support material will be allowed. Information will be provided.

Language of examination

You may write your examination paper in Norwegian, Swedish, Danish or English.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.

Resit an examination

This course offers both postponed and resit of examination. Read more:

Special examination arrangements, use of sources, explanations and appeals

See more about examinations at UiO

Last updated from FS (Common Student System) Nov. 29, 2020 3:14:25 PM

Facts about this course

Credits
10
Level
Master
Teaching
Spring
Examination
Spring
Teaching language
English