Course catalogue doctoral education - VT22

  • Application can be done between 2021-10-15 and 2021-11-15
Application closed
Title Introduction to R - Data Management, Analysis and Graphical Presentation
Course number 2971
Programme 0-Not part of doctoral programme
Language English
Credits 2.5
Date 2021-09-24 -- 2021-10-29
Responsible KI department Department of Laboratory Medicine
Specific entry requirements Basic statistical knowledge (e.g. taken ""Basic course in medical statistics"" or similar course)
Purpose of the course To increase the doctoral student's skills in data analysis and data presentation.
Intended learning outcomes After attending the course, the student will be able to use R for data management, statistical analysis and graphical data presentation. The student will be able to install new functions in R.
Contents of the course R is a powerful software/programming language for data analysis and graphical presentation. R is free-of-charge, and in most cases a useful alternative to commercial statistical software. The programming language is completely text-based, making it challenging compared to software with a graphical user interface. However, it offers greater flexibility, better control over analyses and an automatic documentation of performed analyses.
The course focuses on structure and basic functions of the R programming language . A selection of functions for data management, statistical analysis and graphics is presented. The methods included are commonly used methods in clinical medical science (e.g. t-test, ANOVA, chi2-test, regression and survival analysis, box, line scatter, and bar plots). The course focuses mainly on how the various methods are applied in R and not their theroretical background, underlying assumptions or the theoretical intepretation of the results.
Teaching and learning activities Online video lectures, web-based seminars and web-based practical exercises (individual and group assignments), peer assessment of other students' solutions. The examination takes place on KI campus.
Compulsory elements The practical exercises and the peer assessments of these are compulsory. Students unable to complete the exercises in time due to e.g. illness can get an extension of the deadline.
Examination Written examination.
Literature and other teaching material Recommended course literature (not mandatory):
Andy Nicholls, Richard Pugh, Aimee Gott, ""R in 24 Hours, Sams Teach Yourself"", Sams Publishing, 2015, ISBN 978-0-672-33848-9.
Number of students 15 - 20
Selection of students Selection will be based on 1) the relevance of the course syllabus for the applicant's doctoral project (according to written motivation), 2) start date of doctoral studies (priority given to earlier start date)
More information The course is web-based, with course dates 24/9 (self-studies), 27/9, 29/9, 6/10, 13/10, 20/10, 27/10. The examination is in Huddinge 29/10. Between these course dates, there will be deadlines for mandatory home assignments. Laptop required for programming exercises and examination.
Additional course leader Marine Andersson
Latest course evaluation Course evaluation report
Course responsible Jonatan Lindh
Department of Laboratory Medicine

Avd. för klin. farmakologi, C1:68
Karolinska universitetssjukhuset Huddinge
Contact person Marine Andersson
Institutionen för laboratoriemedicin
08-585 81064