Introduction to R in Geology

General data

Course ID:	1300-WIRGE
Erasmus code / ISCED:	(unknown) / (unknown)
Course title:	Introduction to R in Geology
Name in Polish:	Introduction to R in Geology
Organizational unit:	Faculty of Geology
Course groups:	(in Polish) Przedmiot do wyboru na studiach II-go stopnia na kierunku geologia stosowana (in Polish) Przedmioty do wyboru na II i III roku studiów pierwszego stopnia na kierunku geologia poszukiwawcza (in Polish) Przedmioty do wyboru na II, III i IV roku studiów I-go stopnia na kierunku geologia stosowana (in Polish) Przedmioty do wyboru na studiach drugiego stopnia na kierunku geologia poszukiwawcza
ECTS credit allocation (and other scores):	(not available) Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	English
Type of course:	elective courses
Prerequisites (description):	A fundamental understanding of statistical terminology and inference is advised.
Short description:	R is a free, powerful and flexible software environment designed for data analysis, statistical computing and graphic display. Owing to the open source nature and growing user community, R is one of the most popular choice of tool among university students and scholars working with data. This introductory course provides a basic training in R with a focus on applications to geological sciences, primarily geochemistry and paleontology. The programming basics in R, including the import, inspection and manipulation of data objects, as well as descriptive summaries and basic statistical analysis of data, are covered. The course demonstrates how data can be explored with graphical visualizations and how to generate attractive charts, graphs, and plots. R packages dedicated to the analysis of compositional, circular and spherical data, which are widely used in Earth science research, are presented.
Full description:	This course is an introduction for graduate level geology students who have no previous experience in R and are interested in learning to handle data and perform simple descriptive data analysis. The course assumes no prior knowledge of programming and provides participants with a foundation for developing more advanced research and analytic skills. A fundamental understanding of statistical terminology and inference is strongly advised. Students are required to have a laptop for in-class use. Class sessions are typically divided between introductory lecture/instruction and related practice designed to build programming skills with assistance of the instructor.
Bibliography:	(in Polish) Venables, W.N., D.M. Smith, and the R Development Core Team, 2018. An Introduction to R. 99 p. Teetor, P., 2011. R Cookbook. O'Reilly Media, 436 p.
Learning outcomes:	Upon completion of the course, the student is expected to: - be familiar with R code syntax and main concepts (P2A_W01), - be familiar with RStudio interface (P2A_W02), - have knowledge of R packages and methods for geological data analysis (P2A_W03) - be able to use online resources to address specific problems (P2A_U01), - be confident with data entry, cleaning and preparation for analysis in R (P2A_U02), - have basic R-programming skills developed (P2A_U03), - be familiar with simple manipulation and visualization techniques in R (P2A_U04), - be aware of the importance of proper data analysis and visualization for a career in geology (S2A_U01), - understand the need for individual cultivation of programming and analytic skills (S2A_U02).
Assessment methods and assessment criteria:	The examination of the course consists of two equally weighted components: in-class practical test that evaluates basic skills in R programming and take-home assignments. The take-home assignments are given weekly and are due in one week thereafter.
Practical placement:	none

This course is not currently offered.

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Copyright by University of Warsaw.