Cancelled Applied Biostatistics in Nutrition and Physiology

Course content

Focus will be on standard descriptive methods and parametric statistical models, especially analysis of variance and regression models, as well as more advanced methods including models for repeated measurements; a frequentist point of view will mostly be adopted. It will be a modern approach towards the use of statistical methods, reflecting current practice in nutritional and physiology research as seen in the research activities at NEXS w.r.t. publication of scientific articles and reports. Choice of appropriate statistical models will be a key theme, i.e., how to translate study designs into suitable parametric model specifications, both for randomized controllled trials (e.g., parallel-arm and cross-over trials) and for observational studies (e.g., cohort and cross-sectional studies). Estimation of relevant parameters such as means, differences, and slope coefficients will be of particular relevance. Moreover, methods for improved efficiency and for reducing bias such as relevant adjustments for covariates and confounders  will also be covered. Assessment of uncertainty of estimates by means of confidence intervals and standard errors will also be an integral part of the course; p-values will also be discussed. Statistical methods will mainly be introduced and discussed through reading of selected parts of publications and other relevant literature. The first 6 weeks of the course will consist of lectures and exercises. The last two weeks will consist of project work where participants will reanalyze publicly available data, using the knowledge and skills they acquired during the first 6 weeks. The statistical environment R will be used throughout the course.

Learning outcome


For a number of key study designs used in nutritional and physiology research, the participant will have acquired knowledge on concepts and methods used in applied biostatistics. Specifically, the participant will know 1) how to approach model construction and validation and 2) which quantities are relevant to estimate and report.


The participant will be able to carry out descriptive summaries. For a number of important study designs, the participant will be able to apply state-of-the-art statistical methodology. Methods acquired will be suitable for 1) the quantification of differences between groups in randomized controlled trials and non-randomized studies and 2) the investigation of associations in observational studies.


At the level required for smaller journal articles and master thesis reports, the participant will be able to 1) independently plan, organize, and conduct relevant statistical analyses and 2) critically evaluate and interpret results obtained while accounting for sampling variation in the data.

Lectures, seminars, group work with supervision and exercises.

Course literature will be announced at study start on Absalon.

Academic qualifications equivalent to a BSc degree is recommended.

Continuous feedback during the course of the semester

Comments, ideas, and suggestions when doing article reading and project work.

7,5 ECTS
Type of assessment
Oral examination, 20 minutes
Written assignment, during course
Individual oral examination, 20 minutes examination.
Each student presents a self-selected part of the group report but may be asked about any part of the report during the examination.
Project report and oral exam both count 50% in the final grade.
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Internal grading. More assessors.
Criteria for exam assessment

Please see "Learning outcomes".

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 4
  • Preparation
  • 133
  • Practical exercises
  • 48
  • Exam Preparation
  • 20
  • Exam
  • 1
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 2
No restrictions.
Study Board of Food, Human Nutrition and Sports
Contracting department
  • Department of Nutrition, Exercise and Sports
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Christian Ritz   (4-79707b8147756c7f7a35727c356b72)
Saved on the 29-06-2021

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