Statistical Methods in Medical Research 1 (TN907)
Repetition of basic probability theory and important probability distributions. Graphical presentations. Use of software. Basic epidemiological quantities and briefly about clinical trials. Statistical theory for estimation, confidence intervals and hypothesis testing. Analysis of two independent samples and of paired data. Regression analysis and introduction to variance analysis. Statistical pitfalls.
Course description for study year 2023-2024
Facts
Course code
TN907
Version
1
Credits (ECTS)
5
Semester tution start
Spring, Autumn
Number of semesters
1
Exam semester
Spring, Autumn
Language of instruction
Norwegian
Content
Repetition of basic probability theory and important probability distributions. Graphical presentations. Use of software. Basic epidemiological quantities and briefly about clinical trials. Statistical theory for estimation, confidence intervals and hypothesis testing. Analysis of two independent samples and of paired data. Sample size calculations. Regression analysis and introduction to variance analysis. Statistical pitfalls.
Learning outcome
After having taken this subject one can use basic statistical methods to analyse data. One shall know how to perform the analyses in relevant software, and know which methods are relevant to apply in different situations and how to check their assumptions.
Required prerequisite knowledge
None
Recommended prerequisites
An introduction to statistics.
Exam
| Form of assessment | Weight | Duration | Marks | Aid |
|---|---|---|---|---|
| Individual written assignment | 1/1 | 2 Weeks | Passed / Not Passed |
Course teacher(s)
Course coordinator:
Jan Terje KvaløyCourse teacher:
Ingvild DalenCourse teacher:
Bjørn Henrik AuestadHead of Department:
Bjørn Henrik AuestadMethod of work
Lectures and exercises. The course is given when there is capacity and interest.
Overlapping courses
| Course | Reduction (SP) |
|---|---|
| Statistical Methods in Medical Research 1 (BIO907_1) | 5 |
Open for
Open for PhD students with background in medicine and health science. PhD students with background as master in technology, civil engineering or other natural science backgrounds which include courses in statistics, are not allowed to take the exam.
Course assessment
There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital subject evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.