Statistics for Molecular Biomedicine
Course content
The course is an introduction to statistics aimed for students of medical and biological sciences. An important part of the course is to learn the practical application of statistics using R, which is widely used open source programming language for statistics and data analysis.
Lectures will be a mixture of theoretical parts as well as pratical elements with emphasis on hands-on analysis in R.
Topics include:
- Introduction to the statistical program R
- Descriptive statistics
- Probability and probability distributions
- Study design
- Hypothesis testing/ interval estimation
- Non-parametric methods
- Analysis of variance
- Linear regression and multiple linear regression
- Logistic regression
MSc Programme in Biology
MSc Programme in Molecular Biomedicine
MSc Programme in Environmental Science
Knowledge:
The student will obtain knowledge of
- Statistics for data of biological and/or medical relevance, particularly in the context of the above listed topics.
- The symbolic language of statistics and the corresponding formalism
- Interpretation of statistical results for experimental data
- The statistical programming language R (combined with the optional but highly recommended RStudio)
Skills:
- Set up statistical models for data of biological and/or medical relevance – taking as a starting point models based on the binomial and normal distributions.
- Handle the symbolic language of statistics and the corresponding formalism
- Perform significance testing, p-value calculation and interpretation for simple experimental data, including compute-intensive techniques such as permutation testing.
- Report the results of model set up, data analysis, interpretation and assessment.
- Use R in order to produce basic visualisations, summary statistics and for carrying out necessary calculations of statistical tests for the analysis of biological data.
Competences:
- Formulate scientific questions in statistical terms.
- Carry out the necessary calculations using R.
- Interpret and report the conclusions of a practical statistical analysis.
- Assess and discuss a statistical analysis in a biomedical context.
Lectures and interactive exercises in R, with some supportive flipped elements (at home videos/reading) to provide room for more focus on practical work in sessions. Students are expected to complete regular exercises throughout the course, either individually or in groups.
See Absalon.
Academic qualifications equivalent to a BSc degree is recommended.
The course will involve interactive R sessions, so students will need to bring a laptop computer to lectures. We strongly recommend having R or RStudio installed prior to the first session.
- ECTS
- 7,5 ECTS
- Type of assessment
-
On-site written exam, 4 hours under invigilationContinuous assessment
- Type of assessment details
- The on-site written exam is an ITX exam.
See important information about ITX-exams at Study Information, menu point: Exams -> Exam types and rules -> Written on-site exams (ITX)
Continuous assessment:
Continuous assessment is based on weekly exercises counts for 20% of the grade. To receive full marks on this part, the student should participate in the peer feedback system by providing feedback to other students submissions.
On-site written exam:
Written ITX examination under observation, 4 hours, which counts as 80% towards the grade for the course.
The grade is given as a combination of the 20% for the assignments
and 80% for the exam. The two exams must not be passed seperately. - Aid
- Only certain aids allowed (see description below)
Continuous assessment:
All aids allowed.On-site written exam:
All aids allowed except Generative AI and internet access - Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
- Re-exam
-
Oral examination:
Oral examination, 20 minutes with 20 minutes preparation time.
The oral exam counts for 80% of the final gradeAids: Notes, books and digital books are allowed during preparation.
Written assignment:
The studens must hand in 5 assignments, the 4 best assignments count as part of the grade. the written assignments count 20% of the final grade.Aids: All aids allowed
Criteria for exam assessment
In order to obtain the grade 12 the student should convincingly and accurately demonstrate the knowledge, skills and competences described under Learning Outcome.
Single subject courses (day)
- Category
- Hours
- Lectures
- 35
- Preparation
- 101
- Practical exercises
- 40
- Exam
- 30
- English
- 206
Kursusinformation
- Language
- English
- Course number
- SGBK26002U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 3
- Schedulegroup
-
A
- Capacity
- 80
The number of places might be reduced if you register in the late-registration period (BSc and MSc) or as a credit or single subject student. - Studyboard
- Study Board for the Biological Area
Contracting department
- Globe
Contracting faculty
- Faculty of Health and Medical Sciences
Course Coordinator
- Shyam Gopalakrishnan (20-84798a727e3f788081727d727c837a84797f727f5184867f753f7c863f757c)
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