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Learn the ins and outs of Data Analysis in R!

Students should apply for Data analysis in R to discover the enormous potential of the open-source programming language R and to develop a series of skills and tools to analyse statistical problems of a diverse nature.

Almost every major organizations and universities use R. Google not only uses R but has also written standards for the language that are widely accepted.

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.

We will 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: modelling relationships among the data and predicting future observations. After that, we will extend the linear model to the generalised linear framework, in order to analyse non-normally distributed variables. 

Each day consists of short lectures with examples and exercises in which you apply what you have learned right away. At the end of the course there will be a written assignment which will be graded.

Continue reading below for additional course information.

Andrea Bassi

Andrea Bassi

Andrea Bassi holds a MSc in Engineering Mathematics (Polytechnic University of Milan), with a focus on Applied Statistics. After having worked in Italy as a statistical consultant, he started his PhD training in Biostatistics at the Vrije Universiteit Medical Center, on the BIOMARKER project.

He is currently Senior Data Scientist and R consultant.

"Students should apply for Data analysis in R to discover the enormous potential of the open-source programming language R and for acquiring a series of skills and tools to analyze statistical problems of diverse nature."

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