Data Analysis in R, Short Course | Vrije Universiteit Amsterdam | Amsterdam, Netherlands
8 days
Duration
1100 EUR/full
1100 EUR/full
Unknown
Tuition fee
Unknown
Apply date
Unknown
Start date

About

This Data Analysis in R course from Vrije Universiteit Amsterdam focuses on 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. 

Overview

The first week is devoted to regression analysis, and learning how to use R (i.e. run analyses, visual representation and test assumptions). We start with descriptive statistics and visual representation of data, which is the first step for most statistical analyses. We then introduce the linear regression model, a widely used model with two main purposes: modeling relationships among the data and predicting future observations. 

In the second week, we will extend the linear model to the generalized linear framework, in order to analyse non-normally distributed variables. You will learn how to reduce data dimensions using principal component analysis and how to analyse multi-item scales using confirmatory factor analysis. Multiple item scales are used to validly measure complex constructs, however, in the model you would like to have only one measurement. 

At the end of this Data Analysis in R course from Vrije Universiteit Amsterdam 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.

Programme Structure

Course content

  • Every day consists of short lectures with examples, and exercises in which you apply what you have learnt. 
  • The focus in the exercises and assignment is the coding in R and how to apply and to interpret generalized linear regression models. After class, you work on an assignment in which you integrate what you’ve learnt in the exercises. This assignment will be graded. 

Key information

Duration

  • Full-time
    • 8 days

Start dates & application deadlines

Credits

3 ECTS

Delivered

On Campus

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

Other requirements

General requirements

  • The course is highly intensive both in programming and statistics, which means it will be challenging to those who lack knowledge in both fields. Preferably, you have completed an undergraduate course in statistics, an acquaintance with basic linear algebra, the fundamentals of hypothesis testing, linear regression analysis and statistical tests such as the t-test. 
  • Although we will briefly go over these topics again to refresh your memory, we do not recommend this course to those who learn will these concepts for the first time. For people with programming experience (other languages such as Python), it might be possible to step in with little prior knowledge of statistics.
  • Apart from Bachelor's and Master's students, we also welcome PhD candidates and professionals to apply to the course.

Tuition Fee

To always see correct tuition fees
  • International

    1100 EUR/full
    Tuition Fee
    Based on the tuition of 1100 EUR for the full programme during 8 days.
  • EU/EEA

    1100 EUR/full
    Tuition Fee
    Based on the tuition of 1100 EUR for the full programme during 8 days.
  • Students, PhD students and employees of VU Amsterdam, Amsterdam UMC or an Aurora Network Partner: €735
    • Students at Partner Universities of VU Amsterdam: €995
    • Students and PhD candidates at non-partner universities of VU Amsterdam: €1100
    • Professionals: €1310

Living costs for Amsterdam

1000 - 1500 EUR /month
Living costs

The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.

Funding

If you have been accepted to VU Amsterdam Summer School and have paid the tuition fee, but due to unforeseen circumstances need to cancel, the following refunds will be given:

  • Cancellation before 1 May: 100% of total fee will be refunded
  • Cancellation before 1 June: 50% of total fee will be refunded
  • Cancellation after 1 June: no refund will be given
Costs such as travel arrangement will not be refunded. We therefore suggest to wait with booking your travel arrangements until May.

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Data Analysis in R
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