18 July 2020
on course website
Data Analysis in R - Session 1
With the increasing use of alternative software packages like R in data analysis, now is the time to learn their ins and outs. The large number of active programmers creating R packages makes this an up-to-date programme providing a huge range of statistical analyses. Researchers also use R to write functions for analysing data, or to create professional plots.
This course focuses upon understanding statistical models and analysing the results whilst learning to work with R. As well as introducing the software to newcomers, it presents basic and more advanced statistics using an overarching framework of the generalized linear model. We start with descriptive statistics and simple regression, before moving on to multiple regression.
Many problems in data analysis are related to dimension reduction, from data mining problems such as classification to analyzing survey answers. You will learn how to reduce data dimensions using principal component analysis and how to analyse multi-item scales using confirmatory factor analysis. Additionally, you learn how to treat missing data in various models.
Lastly we will introduce how to create and adjust plots in R. Every day consists of short lectures with examples, and exercises in which you apply what you have learned right away. Each week you are supposed to make an assignment which is graded. The focus in the exercises and assignment is the coding in R and how to apply and to interpret generalized linear regression models. By the end of the two weeks you are acquainted with numerous basic functions available in R can write your own functions and can use attractive plots to present your data.
Meike Morren, Andrea Bassi
Students or professionals with an interest in quantitative data analysis using R. We will use examples from Economics, Social Sciences and Biostatistics. No programming experience is required. PhD students wishing to refresh their knowledge are also welcome. If you have doubts about your eligibility for the course, please let us know. Our courses are multi-disciplinary and therefore are open to students with a wide variety of backgrounds.
At the end of this course you can:
•Evaluate the quality of quantitative data sources.
•Choose the appropriate method for an analysis, depending upon the data source.
•Conduct various statistical tests.
•Analyse data using generalized linear framework.
•Decide when to use latent variable modelling.
•Enjoy your developed programming skills.
Contact Hours: 45
Do you want to make the most out of your summer? You can combine this course with a course in session 2 to create a 4-week summer school.
EUR 1150: The tuition fee includes:
• Airport pick-up service
• Welcome goodie bag
• Orientation programme
• Course excursions
• On-site support
• Emergency assistance
• Transcript of records after completion of the course
An early bird discount of €150 is available for students who apply and pay before 15 March, and students from VU Amsterdam as well as from exchange partner universities will receive a €250 discount. You apply for the discount simply by indicating that you are currently a student at VU Amsterdam or at a partner university in the online application.
There are also discounts for students who attend multiple sessions, combine 2 courses and receive a €200 discount and combine 3 to receive a €300 discount. All courses include excursions. We will also organize trips and excursions as part of our social programme, which is a great way to get to know your fellow students and learn more about Amsterdam and the Netherlands. The social programme is not included in the tuition fee.
Furnished accommodation is available. Various housing options will be offered.
VU Amsterdam Summer School offers three kinds of scholarships: the Academic Scholarship, the Photographer Scholarship and the Vlogger/Videographer Scholarship. More information can be found on the VU Amsterdam Summer School website.Register for this course
on course website