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Data Analysis in R
Interdisciplinary Studies Program
Amsterdam, Netherlands
Dates: early Jul 2027 - early Aug 2027
Data Analysis in R
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Computer Sciences
Instruction in: English
Transcript Source: Partner Institution
Course Details: Level 300
Recommended Semester Credits: 3
Contact Hours: 45
Prerequisites: Successfully completed a statistics course on Bachelor level (hypothesis testing, regression analysis).
DESCRIPTION
With the increasing use of alternative programming languages 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 R suitable for a range of data analysis techniques, from basic hypothesis testing to generalized linear regression, and classification methods such as principal component, cluster and linear discriminant analysis. You will apply what you have learned right away in short exercises using Rmarkdown. You will be graded using an assignment in which you will learn to deal with messy data and integrate the knowledge you obtained in the exercises. The course is highly intensive as it focuses both on interpreting statistics while also learning to program in R. The focus in the exercises and assignment is the coding in R while improving skills in interpreting statistics. 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 statisticians creating R packages makes this an up-to-date program providing a huge range of statistical analyses. Additionally the visualization possibilities in R are endless. This course focuses upon understanding statistical models, analyzing and visualizing 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.
By the end of this course, students will be able to:
- evaluate the quality of quantitative data sources
- choose the appropriate method for analysis, depending on the data source
- conduct various statistical tests
- analyse data using generalized linear framework
- analyse multi-item scales using principal components and factor analysis
- have developed their skills in R programming
Every day consists of short lectures with examples, and exercises in which you apply what you have learnt right away. 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 are supposed to work on an assignment in which you integrate what you've learnt in the exercises during class. This assignment will be graded.
Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course. CEA CAPA's recommended credits are based on the contact hours assigned by Vrije Universiteit Amsterdam (VU Amsterdam): 15 contact hours equals 1 U.S. credit
By the end of this course, students will be able to:
- evaluate the quality of quantitative data sources
- choose the appropriate method for analysis, depending on the data source
- conduct various statistical tests
- analyse data using generalized linear framework
- analyse multi-item scales using principal components and factor analysis
- have developed their skills in R programming
Every day consists of short lectures with examples, and exercises in which you apply what you have learnt right away. 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 are supposed to work on an assignment in which you integrate what you've learnt in the exercises during class. This assignment will be graded.
Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course. CEA CAPA's recommended credits are based on the contact hours assigned by Vrije Universiteit Amsterdam (VU Amsterdam): 15 contact hours equals 1 U.S. credit