Advanced Data Analysis with R
Aims
The open-source software environment R (www.R-project.org) is a powerful platform for data analysis and statistical graphics that has become the global standard in statistical computing. R houses an ever-growing extensive collection of tools for statistics and data analysis – an attractive basis for thorough exploration of your data. Furthermore, it provides a powerful programming language coupled with flexible graphical capabilities.
In this follow-up to the introductory course (Introduction to Data Analysis with R), students will continue to learn more of R's capabilities for extracting knowledge from data. Basic programming concepts in R will be covered, such as control structures, loops and functions, enabling students to automate repetitive data analytic tasks. Finally, using R for scraping data from the web will be discussed, with students gaining practical experience of collecting such data. Upon completion of the course, you will be able to use R for advanced analytic tasks to improve the quality of your research.
Information
- Generalized linear models, such as logistic regression
- Cluster analysis, including hierarchical and optimization-based approaches
- Programming in R: control structures, loops, functions
- The apply()-family of functions, and the plyr package
- Collecting web data with R
Assessment
- Homework in the form of practical analyses in R, which need to be prepared as an R script.
- Presentation and discussion of the prepared R script in the form of a short report.
Materials
Course notes will be provided.
There are no prescribed books. The following books are recommended to interested students as further reading material:
- R.I. Kabacoff (2015). R in Action. 2nd edition. Manning.
- P. Dalgaard (2008). Introductory Statistics with R. 2nd edition. Springer.
- S. Munzert et al. (2015). Automated Data Collection with R. Wiley.
Additional info
The course will be taught in English and is limited to 25 participants. Students are required to bring their own laptops to class (R and RStudio can be installed for free). The course Introduction to Data Analysis with R is a prerequisite for this course. Exemptions from this requirement can be requested from the course's contact person.
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More information and detailed timetables can be found here.
ERIM PhD candidates and Research Master students can register for this course via SIN Online.
External (non-ERIM) participants are welcome to this course. To register, please fill in the registration form and e-mail it to miizuka@rsm.nl by four weeks prior to the start of the course. Please note that the number of places for this course is limited. For external participants, the course fee is 260 euro per ECTS credit.
