05 Dec Introduction to R
- Day 3,4
24/01/2022 - 25/01/2022
1:00 pm - 5:00 pm
- Day 5
1:00 pm - 5:00 pm
statistics course | level: beginner |
for questions related to this event, contact firstname.lastname@example.org
affiliation: Ghent University
R is an environment for statistical computing and graphics, which is becoming increasingly popular as a tool to get insight in often complex data. While somewhat similar to other programming languages (such as C, Java and Perl), R is particularly suited for data analysis because ready-made functions are available for a wide variety of statistical (classical statistical tests, linear and nonlinear modeling, time-series analysis, classification, clustering, ...) and graphical techniques.
The base R program can be extended with user-submitted packages, which means new techniques are often implemented in R prior to being available in other software. This is one of the reasons why R is becoming the de facto standard in certain fields such as bioinformatics and financial services. This course introduces the use of the R environment for the implementation of data management, data exploration, basic statistical analysis and automation of procedures.
The course starts with a description of the R GUI, the practical use of R studio and an overview of basic data structures. The application of standard procedures to import data or to export results to external files will be illustrated.
Creation of new variables, subsetting, merging and stacking of data sets will be covered in the data management section. Exploration of the data by histograms, box plots, scatter plots, summary numbers, correlation coefficients and cross-tabulations will also be performed.
Simple statistical procedures that will be covered are:
- comparison of observed group means (t-test, ANOVA and their non-parametric versions)
- linear regression
Practical sessions and specific exercises will be provided to allow participants to practice their R skills in
interaction with the teacher.
The course is open to all interested persons. Knowledge of basic statistical concepts and experience with other
programming languages are considered advantages, but not required for learning the R language.
R For Dummies. Andrie de Vries, Joris Meys. ISBN: 978-1-119-96284-7. Jun 2012. 406 pages
Grolemund, G., & Wickham, H. (2017). R for Data Science. O’Reilly Media
PricesPhD's and postdocs of a Flemish university: free
Other academics & Non-profit/Social sector: €375
Private sector: €1000