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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
- 11 days
Start dates & application deadlines
We did our best, but couldn't find the next application deadline and start date information online.
More details
Early Bird Deadline: 15 March
Language
English
IELTS 6.5
TOEFL® IBT 92
Credits
3 ECTS
Delivered
On Campus
Disciplines
Statistics Computer Sciences Data Science & Big Data View 8 other Short Courses in Statistics in NetherlandsAcademic requirements
We are not aware of any academic requirements for this programme.
English requirements
IELTS 6.5
TOEFL® IBT 92
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.
- It is not necessary to provide us with proof of your English. We do expect your English to be sufficient to understand classes and course literature.
Tuition Fee
To alway see correct tuition fees
-
International
950 EUR/fullTuition FeeBased on the tuition of 950 EUR for the full programme during 11 days. -
EU/EEA
950 EUR/fullTuition FeeBased on the tuition of 950 EUR for the full programme during 11 days.
- VU Students/PhD candidates and employees of VU Amsterdam* or an Aurora Network Partner: €650
- Students at Partner Universities of VU Amsterdam: €500
- Students and PhD candidates at non-partner universities of VU Amsterdam : €950
- Professionals: €1150
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
Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.
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