Kurskatalog forskarutbildning  VT22

Startsida
Ansökan kan ske mellan 20211015 och 20211115
Application closed
Skriv ut
Skriv ut
Titel  Get started with R – Programming Basics, Data Analysis and Visualisation 

Kursnummer  5300 
Program  0Inte del av forskarutbildningsprogram 
Språk  Engelska 
Antal högskolepoäng  3.0 
Datum  20210823  20210906 
Kursansvarig institution  Institutionen för neurobiologi, vårdvetenskap och samhälle 
Särskild behörighet  
Kursens syfte  The course is practical and aims at teaching students how to:
Use the programming environment R and RStudio, which includes installation, how to handle errors, problem solve and access helper documents. Use basic concepts of programming, such as data types, logical and arithmetic operators, if else conditions, loops and functions. Use common R packages to perform basic statistical analysis (e.g., ttest, chi2test, correlation) and visual presentation (e.g., boxplot, histogram and heatmap) of data in R. 
Kursens lärandemål  After attending the course the student should know:
• How to download, install and navigate R and RStudio • How to solve common problems arising from data formatting and handling • Common programming concepts and how to employ them in R • How to import data and packages in R • How to use R for basic statistical analysis and visual presentation of data 
Kursens innehåll  Course participants start the course by installing and familiarising with the R and RStudio environment. This includes version control, as well as structuring and documenting code for publication. Next, basic concepts shared between all programming languages are introduced, such as data types and operators. Students will also learn how to use recommended naming conventions, syntax and how to comment code. Methods for importing packages and data is then introduced and students will learn how to search for help and get examples of common problems that may arise. Finally, students will practice using packages for data management, statistical analysis and visual presentation. Methods include distribution tests, poweranalysis, ttest, chi2test, correlation, boxplot, scatterplot and bar plot. Visual presentation will mainly use the ggplot2 package, providing a good example of objectoriented programming in R. Throughout all lectures focus will be on application and understanding of the methods used, not statistical assumptions or interpretation of the results. Examples will primarily be taken from experimental research and tasks will use dataframes available upon installation of R. However, when possible students are encouraged to use their own data.
The last day of the course can either be used to continue to apply R on own data or to learn procedures that can be performed with R which most other statistical software’s cannot. Such as, managing folders and files, querying databases and importing codes and algorithms. 
Arbetsformer  Distance learning with online interactive lectures. Group and individual exercises where a teacher will be available to help. Assignments and Canvas quizzes that the student completes on their own. Reviewing other students’ code and interaction with other students. Individual project work. Four days each week will consists of lectures in the morning introducing concepts and tasks in the afternoon, where these concepts are put to practice. The last day of each week will be a larger exercise where the student is required to combine introduced concepts into a whole. This exercise will be reviewed by a fellow student who will have the opportunity to comment on ways to improve the work. The 11th (last) day is optional and described in the previous paragraph. 
Obligatoriska moment  Canvas quizzes and tasks. Individual projects and reviews of other students’ project. Participation during project presentation and review.
Students who miss obligatory elements will complete extra tasks associated with the specific element. Course participants unable to participate during the project presentation will have the presentation for the course administrator but will miss the opportunity to get their work reviewed by other participants. 
Examination  Project presentation and review. 
Kurslitteratur och övriga läromedel  Literature recommendations (not required):
Michael J. Crawley, “Statistics: An Introduction Using R”, Wiley, 2014, ISBN 9781118941096 For students used to Excel another alternative is (although it deals primarily with data manipulation): John L Taveras, “R for Excel Users: Introduction to R for Excel Analysts”, CreateSpace Independent Publishing Platform, 2016, ISBN 9781500566357 
Antal studenter  15  25 
Urval av studenter  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) 
Övrig information  From Monday to Thursday, the course consists of Zoom lectures in the morning (8:30  12:00) and tasks that can be completed alone in the afternoon. One course leader will be available during afternoons to help any student who experiences difficulty completing the tasks. On the first Friday students will get an exam assignment, which will be presented and reviewed on the second Friday. The 11th day of the course is not obligatory, but intended for students who want to learn about functions available in R that most other statistical software can not do. 
Ytterligare kursledare  Modjtaba Zandian 
Senaste kursvärdering  Not available 
Kursansvarig 
Billy Langlet Institutionen för neurobiologi, vårdvetenskap och samhälle +46762033996 billy.langlet@ki.se 
Kontaktpersoner   