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The R course of the MARUG will again be offered in cooperation with a partner. This course will be given in English. During this course, we will introduce you in R and we will guide you through all the steps needed to process raw data into a (predictive)model.
The course will consist of 5 modules (the first module you can complete at home). At the end of the course, you will have improved analysis capabilities, directly applicable knowledge and you will be able to build your own model. Furthermore, you will go home with an official certificate. The costs of the course are 50 euros. You can still participate!
The first module is an introduction to the language R. You’re going to get acquainted with fundamentals of this statistical modelling language. You’ll learn what vectors, data frames and matrices are and how to handle factors. Furthermore, you’ll extract basic summary statistics and create some graphs.
We’ll start by giving an introduction to Rstudio, which is an IDE for R. We’ll show you how to set up projects and how to install packages. We’re going to load, explore and subset data and create some more graphs.
In this third module we’ll talk about data types and how to handle numerical values which are actually categorical. We’ll discuss how to handle missing values, what the apply-function does in data frames and we’re going to create some new variables by using if-then-else statements, computations and transformations.
This module focuses on necessary data preparation steps for modelling, we’ll dive deeper into handling outliers. We going to discuss imputation methods for missing values for different types of variables. And finally, we’re going to focus on correlations, correlation plots and correlated predictor variables (multicollinearity).
Now you’ve learned how to process data, it’s time to start modelling. We’re going to build a decision tree, just because it’s so easy and gives you a lot of insights in patterns in the data. Also we’re going to build a logistic regression and show you how you can build practically every model you want. Of course model evaluation can’t be left out, so we’ll discuss classification tables, AUC and create some plots.
This course is given on the following dates:
- 12th of November (Online, at home)
- 19th of November 18:00h - 21:00/22:00h 5415.0032
- 26th of November 18:00h - 21:00/22:00h 5415.0032
- 3rd of December 18:00h - 21:00/22:00h 5415.0032
- 10th of December 18:00h - 21:00/22:00h 5415.0032