Netherlands, Nijmegen

Quantitative Data Analysis with R

when 5 August 2019 - 9 August 2019
language English
duration 1 week
credits 2 ECTS
fee EUR 600

This is an essential crash course for those who need to perform quantitative data analysis, from descriptive statistics up to regressions, and want to do it in open-source R software (with RStudio).

This course will be most useful to students and researchers who are already familiar with statistics and descriptive data analysis and who would like to learn and practise the skills of data analysis in R. R is a powerful statistical software that is free, open-source, available for all popular operating systems, fast to implement new analysis techniques, and has a burgeoning multi-language community of users across the world. We will use RStudio, a friendly interface that is easier to learn for beginning users. Within this course, we will learn how to describe a data set, visualise it, and model relationships between variables in R. The focus will be on the way to process data, types of objects and variables, and standard practices and packages for data analysis in R. The course finishes up with regressions, so that you can practice one of the most widely used types of statistical models.

The course will consist of lectures with slides and practical sessions of data analysis. Participants are expected to bring their own laptops to class. All software is free and can be installed on site.
- Day 1 will focus on the way R deals with various types of data and simple descriptive statistics.
- Day 2 will focus on association tests between variables, including chi-square and correlations.
- Day 3 will deal with comparisons between two or more groups, which will use t-test and one-way analysis of variance, and introduce linear regressions in R.
- Day 4 will continue with the diagnostics of linear regressions, discuss interactive effects in linear regressions and introduce binary logistic regressions.
- On Day 5, we will finish with an outlook of other popular techniques of data analysis in R, including cluster analysis and factor analysis.

To obtain credits for this course, participants can sit a take-home test where they will solve a few data analysis problems in R. This course is an ideal starting point if you have some experience in statistics with any software but you have considered working in R.

Course leader

Anna Shirokanova
Senior research fellow
Laboratory for Comparative Social Research
NRU Higher School of Economics
St. Petersburg, Russia

Olesya Volchenko
Junior research fellow
Laboratory for Comparative Social Research
NRU Higher School of

Target group

Advanced Bachelor
Master
PhD

This course is intended primarily for those who have some knowledge of statistics and would like to learn how to analyse data with quantitative methods of analysis in R, a popular open-source statistical software. The course is a gentle introduction that will help you adapt to R and learn how to implement statistical tests for the purpose of your research.

Course aim

After this course you are able to:

Describe and visualise your data and relationships between variables in R,
Evaluate relationships in the data with various statistical tests in R,
Evaluate and report linear regressions with R.

Fee info

EUR 600: Normal fee

Scholarships

€ 540 early bird discount – deadline 1 March 2019 (10%)
€ 510 partner + RU discount (15%)
€ 450 early bird + partner + RU discount (25%)