Syllabus database for doctoral courses
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Syllabus database for doctoral courses
SYLLABI FOR DOCTORAL COURSES
Swedish title | Introduktionskurs i R |
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English title | Introduction to R |
Course number | 2958 |
Credits | 1.5 |
Responsible KI department | Institutionen för medicinsk epidemiologi och biostatistik |
Specific entry requirements | Biostatistics I: Introduction for epidemiologists or corresponding courses. |
Grading | Passed /Not passed |
Established by | The Board of Doctoral Education |
Established | 2016-09-08 |
Purpose of the course | The purpose of this course is to introduce students to using the R statistical software to perform basic to intermediate statistical data analysis in a replicable manner. |
Intended learning outcomes | After successfully completing this course, students are expected to be able to: - explain basic concepts of the R language and environment, the online- and offline sources of documentation for R, and basic concepts of data management and workflow in a standard statistical analysis, - run a standard statistical analysis interactively within the R environment, - formalize and document such a standard analysis as a stand-alone R script, - produce graphical representations, as part of reporting their analysis, - interpret their scripts for potential simplifications via functional implementation, - find, install and compare extension packages for unfamiliar statistical applications. |
Contents of the course | The course will cover the basic elements of a standard statistical workflow: reading data into R; pre-processing and quality assessment of data via numerical and graphical methods; descriptive statistics via summary measures, tabulations and graphics; basic statistical inference in terms of significance testing and confidence intervals; specification, fitting & diagnosis of regression models; exporting and reporting results from the previous steps. The course includes an introduction to the Rstudio integrated development environment to provide a common framework for interactive and scripted analysis. The extensibility of the R system will be demonstrated by example. |
Teaching and learning activities | Course days will be organized around a common theme, with concepts and background covered in the mornings via presentations, demos, in-class exercises and discussions, and practical application via individual and small-group lab exercises in the afternoons. Formative assessment will be integrated via in-class quizzes and lab reviews. |
Compulsory elements | The individual examination (summative assessment) is compulsory. |
Examination | Students will perform an open-book examination based on practical application of the concepts presented during the course to realistic data sets and problems. Students who do not pass the examination will be offered a second examination within two months from the end of the course (excluding academic holidays). |
Literature and other teaching material | 1. Lecture notes and code examples as provided by the course 2. Official R manuals and documentation available within the software 3. Selected material from the contributed documentation available from the Complete R Archive Network at https://cran.r-project.org/other-docs.html |
Course responsible |
Alexander Ploner Institutionen för medicinsk epidemiologi och biostatistik 0852482329 Alexander.Ploner@ki.se |
Contact person |
Gunilla Nilsson Roos Institutionen för medicinsk epidemiologi och biostatistik 08-524 822 93 gunilla.nilsson.roos@ki.se |