This module is currently full. There is a waiting list for this module. If you want to participate, please send us a filled out registration form. When places free up people on the waiting list will be contacted in the order they chronologically joined the waiting list.
Type of course
This is an on campus course. However, should safety restrictions issued by UGent due to the corona crisis make on campus classes impossible, the course will instead be taught online.
Dates
October 13, 20 and 27, November 3, 2020, from 5.30 pm to 9 pm. Please note: the deadline for UGent PhD students who want a refund to open a dossier on the DS website(Application for Registration) is September 11, 2020.
R is a flexible environment for statistical computing and graphics, which is becoming increasingly popular as a tool to get insight in often complex data. While in some ways 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, timeseries 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 before 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 (Bioconductor) 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.
It starts with a description of the R GUI, the use of the command line 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 be performed.
Simple statistical procedures that will be covered are:
comparisons of observed group means (t-test, ANOVA and their non-parametric versions) and proportions
test for independence in 2-way cross tables and linear regression (focusing on the R-implementation of the statistical methods that are the subject of other modules of the statistics series)
Finally, installing new packages and automation of analysis procedures will also be discussed.
Practical sessions and specific exercises will be provided to allow participants to practice their R skills in interaction with the teacher.
Target audience
This course targets professionals and investigators from diverse areas with little to no R-programming experience who wish to start using R for their data manipulation, data exploration or statistical analysis.
Exam
There is no exam connected to this module. Participants receive a certificate of attendance via e-mail at the end of the course.
Incorporation in DTP and reimbursement from DS for UGent PhD students
As a UGent PhD student, to be able to incorporate this 'transferable skills seminar' in your Doctoral Training Program (DTP) and get a refund of the registration fee from your Doctoral School (DS) you need to follow strict rules: please take the necessary action in time. The deadline to open a dossier on the DS website (Application for Registration) for this course is September 11, 2020. Please note that opening a dossier does not mean that you are enrolled. You still need to enrol via the registration form on this site.
Course prerequisites
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.
Teacher
Dr. Jef Vlegels is a sociologist and statistician working at Ghent University as a post-doc (CHEGG research group) and as a lecturer at Flames training network for Methodology and Statistics. In his research he specializes in quantitative methods for the social sciences, with a specific focus on Social Network Analysis. He is an experienced lecturer in methodology and statistics, with previous experience in introductionary courses as well as advanced specialized courses for Bachelor, Master and PhD students.
Course material
Copies of slides.
Book recommendations
A recommended handbook for further study is "R for Dummies", J. Meys and A. de Vries, 2nd ed. (2015), Wiley, ISBN 978-1119055808. Those who wish to explore R further after the course can order it online or at their local book store. Please note that you do not need a copy of this book to follow the course.
Fees
Different prices apply, depending on your main type of employment.
Employment
Module 1
Industry/Private sector1
390
Non-profit, government, university outside AUGent2
195
(Doctoral) student outside AUGent2
125
1If three or more employees from the same company enrol simultaneously for this course a reduction of 10% on the module price is taken into account.
2 AUGent staff and AUGent doctoral students who pay through use of an SAP internal order/invoice can participate at these special rates
