For students attending the course Quantitative Research and Methods 2 course code 4GB008
This course progresses on earlier courses by emphasising how measures of disease occurrence (e.g., incidence and prevalence) and associations (e.g. risk ratios, incidence rate ratios, odds ratios) can be estimated using statistical models, and how statistical methods can be used to overcome biases in epidemiological studies. Students will interpret and present output from statistical analysis in written, tabular, and graphical forms.
Syllabus
Welcome to the course Quantitative Research and Methods 2.
The course begins on May 11, 2026.
A very warm welcome to all of you. We look forward to meeting you on May 11 at 9:00 AM at Charles (ground floor, Widerströmska Huset, Tomtebodavägen 18A).
The course will take place on Campus Solna in Widerströmska Huset over four weeks. For more details and the course schedule, please read the welcome letter carefully, which will be sent to you three weeks before the course starts.
If you anticipate any difficulties attending the course, please contact us in advance.
Registration is compulsory to secure your place and attend the course. You must register via Ladok:
https://www.student.ladok.se/student/loggain
The registration period opens one week before the course starts and closes two days after it begins.
More information:
https://education.ki.se/student-at-ki/new-student/web-registration
Direct link to LADOK: https://student.ladok.se/student/app/studentwebb/
The registration period for this course in Ladok is 2026 05 04 – 2026 05 12.
For further information about this course, please contact:
Henrike.habel@ki.se
Course Leader
Nora.espahbodi@ki.se
Course administrator
The course aims to provide students hands-on data analysis skills using statistical software, including:
- linear regression
- logistic regression
- methods to handle time to event data
- estimation methods (maximum likelihood, least squares)
- hypothesis testing and confidence intervals for regression coefficients
- variable selection and model comparison
- absolute and partial predictions
- ethical guidelines (e.g. by the International Statistical Institute) and quality standards (e.g. STROBE)
Schedule
Course evaluation and course analysis
Course evaluation and course analysis will be published one month after the end of course.
Contact information
Nora Espahbodi
Course Educational officer
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