Course catalogue doctoral education - VT24

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Title Statistics with R - from data to publication figure
Course number 2953
Programme 0-Not part of doctoral programme
Language English
Credits 3.0
Date 2018-04-25 -- 2018-05-18
Responsible KI department Department of Laboratory Medicine
Specific entry requirements none
Purpose of the course Do you need to turn data into a publication figure? We offer tools and confidence for the student to independently select a statistical method for research questions in their field. Furthermore we teach a structured way to discuss their choice efficiently with a professional statistician. The course is practical and includes implementing a basic statistical analysis in R, the leading statistical programming language in bioinformatics and medical science. Students can bring data from their own research project, or work on data from the course.

Intended learning outcomes By the end of the course the student should be able to:

* download and install the latest versions of R and Rstudio.
*know where to look for help when working in R.
*know how to import data into R.
*use R for basic analysis and presentation of data in their field.
*select statistical method and motivate the choice using a structured approach.
*communicate efficiently with a statistician about their choice of statistical method.

Contents of the course Basics of R. Download, install, import data, basic analysis, how to get help.
Learn to speak statistics. A structured approach to selecting statistical method and communicating with a statistician.
Practice how to go from data to publication figure using data from your project or more or less friendly data offered by the course.

Teaching and learning activities Distance learning with online lectures, quizzes and interaction with other students.
Campus lectures and computer work using your own computer.
Individual project work.

Compulsory elements Online quizzes and tasks. Active participation in online discussions (asynchronous, not bound to a particular time of day). Active participation in computer lab sessions. Written report including executable code. Active attendance in seminar. Compulsory attendance approximately four afternoons and one day.

Examination Online examination. Participation in labwork and seminar. Written project work with executable code.
Literature and other teaching material The literature is recommended , but not compulsory. Most information can be found online for free.
Dalgaard - Introduction to statistics with R
Crawley - Statistics an introduction using R
Number of students 20 - 30
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) date for registration as a doctoral student (priority given to earlier registration date)
More information The course starts with a kickoff meeting April 25 at 0930-1200 helping you to get started with the distance learning part of the course. The distance learning is at your own pace, but should be finished by May 13. For the novice, the distance learning corresponds to one week full time studies. May 14 through 18 are scheduled full days with lectures, work shop, preparation time and poster presentations. All scheduled activities take place in Huddinge.
Additional course leader Eva Hagel
Latest course evaluation Course evaluation report
Course responsible Andreas Montelius
Department of Laboratory Medicine
0704158108
Andreas.Montelius@ki.se

Karolinska University Hospital

14186
Stockholm
Contact person Eva Hagel
Institutionen för lärande, informatik, management och etik

eva.hagel@ki.se