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PNG0096

Avancerad datahantering i R

The course will be split across the three themes of the learning outcomes above. In each theme, the students will be given some learning materials (online video and example code) and a task to complete. There will be a non-compulsory online question and answer session for each theme, before a class-wide workshop where students will present their work.



1. Write reproducible code

Individual study: Here students will practice how to write reproducible code. Students will consult style guides and then be given a simple exercise using one of two sample data sets. The idea here is that the functions used in the exercise should already be familiar to the students, but that the students will write the code in a reproducible way. Students will create a new (or use an existing) GitHub account to upload their work to a course project site. Students will then be assigned into groups of two and will have to use each other’s code to first re-run the original exercise, and then use the same code to complete the exercise with the other data set. Students will discuss together how their code could be improved to become more understandable and reproducible.

Workshop: Each pair will present the results of their exercise, and teachers will lead a discussion based on the students’ experiences.



2. Confidently manipulate data and R-objects

Individual study: Study material will teach the students different ways to manipulate large and heterogeneous datasets in a reproducible way. Students will then be given one of two data sets and be asked to produce a set of specific figures. As in the first theme, students will be assigned to groups of two and check and comment on each other’s code for clarity and reproducibility.

Workshop: Each pair will present the results of their exercise, and teachers will lead a discussion based on the students’ experiences.

Kursplan och övrig information

Kursfakta

Ämne: Matematisk statistik
Kurskod: PNG0096 Plats: Uppsala Distanskurs: Ja Undervisningsspråk: Engelska Ansvarig institution: Institutionen för ekologi Studietakt: 100%