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We’re happy to announce that, next to our Summer School program, we will offer a Winter School program at the end of January/beginning of February.  The Methods and Statistics Winter School will, this year, take place in the week of 31 January – 3 February and consist of seven one-day (on-location) courses, which are introductory courses to (open-source) statistics programs and open-source programming languages.

Below, you find the Methods and Statistics Winter School courses.

Monday 31 January 2022

 
This course is a compact 1-day workshop introducing Mplus. We will focus on preparing data for Mplus, introducing common model syntax, avoiding common mistakes, interpreting output, and dealing with common error messages. (course code: S001)

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In this course, students will learn what R is and how it differs from other statistical software packages and programming languages. They will learn the basics of data I/O, manipulation, and visualization in R. (course code: S002)

Tuesday 1 February 2022

This course is tailored to lecturers and researchers who want learn what the bachelor students of FSBS at the UU learn about JASP and (Bayesian) hypotheses evaluation (and a little bit more). This course is free of charge for UU employees. (course code: S003)

Wednesday 2 February 2022

In this course, students will learn how to apply linear regression techniques in R. We will cover (multiple) linear regression, categorical predictor variables, moderation, prediction, and diagnostics. (Course code: S004)

This workshop is an introduction to the Python programming language and in particular is geared towards people new to the language and who may, or may not, have experience with other programming languages. (course code: S005)

Thursday 3 February 2022

 
In this course, participants will learn how to apply text mining methods on text data and analyze them in a pipeline with machine learning and natural language processing algorithms. (course code: S006)

In this workshop, we will discuss principled methods for treating missing data and how to apply these methods in R. (course code: S007)

On you can find an overview of all Summer school courses offered by the Department of Methodology and Statistics.