For students attending the course Applied biostatistics (7,5 hp) course code 4BI108

The goal of the course is to equip the future Masters in Biomedicine with basic tools for understanding statistics in research - their own as well as others.

Syllabus

Information about the course

The content of the course is grouped into three parts:

Introduction: basic statistical terms and concepts (descriptive statistics, probability, central limit theorem, confidence intervals, and statistical tests).

Regression modeling: linear and logistic regression, multiple regression, the role of covariates, and causal inference.

Survival analysis: time to event outcomes, censoring, estimating survivor curves, comparing survivor curves, and proportional hazards regression

The course is strongly focused on application and analyzing realistic data using the statistical software R. Consequently, almost half the planned activities will have you work on problems and examples, either on your own or in small groups. 

Schedule

The schedule will be presented here two weeks before the course starts. Students will get access to the course web in Canvas just before the course starts.

The next course will start in October 12, 2022. 

Examination

The examination will be held at the time specified in the schedule. 

Further information will be given during the course.

Attendance, course material and software

You are required to register for this course in Ladok,  please contact the course administrator if there is any questions regarding this.

You will use the open-source statistical software R, which is freely available from the CRAN website. We will give a short introduction on using R with a simple graphical user interface at the beginning of the course. Feel free (actually, feel encouraged) to bring your own laptop (we will help you with installing R if you have problems).

Video demo of installation (8 min) 

Literature

There is no dedicated course book: while there is no lack of excellent introductory biostatistics books, most are written for either clinical or public health researchers, and stress somewhat different aspects. Consequently, we try to put everything you need to pass the course into our handouts.

For a basic introduction, we recommend the OpenIntro Statistics text book, which is freely available in electronic format from http://www.openintro.org/stat/textbook.php It's very thorough and keeps formulas to a minimum, but has no special focus on life sciences (statistics rather than biostatistics). If you do not mind the occasional economy- or psychology problem, it is quite readable.

For some more directly relevant complementary reading, the following books are available from the KI Library. They are well written, with excellent examples from biomedical research:

DG Altman: Practical Medical Statistics

M Bland: An Introduction to Medical Statistics

M Pagano: Principles of Biostatistics

B Rosner: Fundamentals of Biostatistics (very detailed)

P Dalgaard: Introductory Statistics with R (software specific) 

Preparation & self-evaluation

By requirement of the Biomedicine programme, this is an advanced-level course. This means that participants should have been exposed to (most of) the content in Module 1 (Introduction/Recap) already previously, preferably in a university-level introductory statistics course. If you are uncertain whether you should undertake some extra preparation (reading) prior to course start, please have a look at the Biostatistics Course self assessment further down.

Besides detailed description of course requirements, this documents also contains a nifty multiple-choice self-assessment test.

Contact

Matteo Bottai

Course direcor
C6 Institute of Environmental Medicine

Kamilla Sagrelius

Course administrator

Malin Sandell

Study Counsellor
C7 Department of Learning, Informatics, Management and Ethics

Schedule fall 2022

Biostatistics Course self assessment

Course evaluation