Introduction to R
The open software package R is becoming more and more popular. Many new statistical tools are developed within this package. Yet, dealing with R requires quite some effort and stamina. This course provides an introduction to the R software.
- Target group
- PhD candidate
- Frank Busing (Researcher)
Participants will learn to work with R and R-Studio, the most popular R environment.
- Day 1
Simple data and simple functions are introduced first. After complex data structures and complex (vectorized) functions, participants need to mimic well-known statistical techniques, commonly performed with SPSS: t test, chi-square test, linear regression analysis, one- and two-way AN(C)OVA, principal component analysis, multidimensional scaling, factor analysis, item response theory models, and some non-parametric tests.
- In between days
The participant may try the techniques on their own data.
- Day 2
Another strong point of R is examined in depth: Graphics. We will introduce scatter plots, bar charts, boxplots, Q-Q-plots, and multi-panel plots. The course concludes with programming in R. The participants will learn how to create their own functions using statements like if-the-else, while, repeat, for, in, break, next, and so on.
The participant is able to:
- work out problems with R,
- find proper help, and
- gain understanding and improve R skills, all by her or himself.
We will only help in the process by supplying materials, assignments, and advice.