Introduction to R (for participants with some prior knowledge in command-line programming)

R is a powerful and versatile computing environment, widely used by statisticians, economists, and political scientists.

R is developed by its users, and researchers from many different fields have contributed to making R into the powerful statistical program it is today. This means that users can write their own R code, or adjust existing code according to their needs, and share this code with others. But it also means that there are a vast number of statistical tools and methods implemented in R, and we will only scratch the surface of R’s vast potential in this short introductory course. However, I aim to provide you with enough knowledge of how R works to learn new techniques yourself, and/or follow other courses in R.

First session

I'll give an overview of how R works and which tools are available to facilitate working with R (in particular RStudio).

Then we will learn about objects in R, how they (or a subset of their elements) can be accessed and manipulated, and how they can be transformed into datasets for further analysis. I will cover reading in data from other data formats such as SPSS and STATA, as well as how to save data.

Once we are familiar with data generation and data access, we will learn how to merge different datasets, and bring them into the desired data format.

Second session

We will start analysing the data, first using simple summary commands and descriptive statistics, but also using various tabulating tools available in R.

Then we will implement regression analysis in R, and access various elements of our statistical models for further analysis.

We will also cover data transformation and how to deal with special values in R.

Final session

I will talk about the powerful graphic tools provided by R.

We will use the basic plot function that comes with the standard R distribution, but I will also talk about other graphics packages such as lattice and ggplot2.

Finally, we will briefly talk about writing our own simple functions in R.

By the end of the course, you should have knowledge of the basic functions of R, sufficient to follow other Winter School courses which require this basic knowledge.

You should also know how to get help, and thus how to learn for yourself techniques not covered during the course.

Some basic knowledge of R, or any other command-line programming language such as Stata or SPSS.

If you are an absolute beginner, take course WA105(A), taught by Thorsten Schnapp.

The two courses are essentially the same: both start with the absolute basics, but in this course we will progress faster and cover more ground.