Syllabus database for doctoral courses
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Syllabus database for doctoral courses
SYLLABI FOR DOCTORAL COURSES
| Swedish title | Statistik med R - från data till publikationsfigur |
|---|---|
| English title | Statistics with R - from data to publication figure |
| Course number | 2953 |
| Credits | 3.0 |
| Responsible KI department | Department of Laboratory Medicine |
| Specific entry requirements | none |
| Grading | Passed /Not passed |
| Established by | The Board of Doctoral Education |
| Established | 2018-09-19 |
| 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. The course is practical and includes implementing a basic statistical analysis in R, the leading statistical programming language in bioinformatics and medical science. Furthermore, we give a brief introduction to visualization in R, with a focus on R/ggplot2. 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. Visualization of data. 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. Digital poster presentation of individual work. |
| Compulsory elements | Online quizzes and tasks. Participation during Poster Presentation day. |
| Examination | Poster presentation and peer review. |
| 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 Wickham - ""ggplot2: Elegant Graphics for data analysis"" |
Course responsible |
Johan Boström Department of Laboratory Medicine johan.bostrom@ki.se |
| Contact person |
Maria Westerstahl Department of Laboratory Medicine Maria.Westerstahl@ki.se Eric Rullman Department of Laboratory Medicine Eric.Rullman@ki.se |
