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 | Institutionen för laboratoriemedicin |
| Specific entry requirements | |
| Grading | Passed /Not passed |
| Established by | The Committee for Doctoral Education |
| Established | 2020-08-31 |
| 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.
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| 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.
Lectures at campus or online via ZOOM. Individual project work using your own computer. Digital poster presentation of individual work. |
| Compulsory elements | Online quizzes and tasks. Participation during Poster Presentation day.
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| 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 |
Alen Lovric Institutionen för laboratoriemedicin alen.lovric@ki.se |
| Contact person |
Maria Westerstahl Institutionen för laboratoriemedicin Maria.Westerstahl@ki.se Eric Rullman Institutionen för laboratoriemedicin Eric.Rullman@ki.se |
