Monday – Classes from 09:00 to 17:00 - “Introduction to R”
Session 1: Introduction (morning)
In this session I will kick off with a lecture about the rationale of R as a language. We will discuss the reasons for each participant for attending the course, so that we can target parts of the course on the specific personal needs. I will use this introduction to motivate the four days of the course by introducing the potentials of R. Then, I will explain basic principles and terminology of R.
Session 2: Introduction (afternoon)
During the afternoon we will go through some of the basic principles of R, including packages, commands, reading and writing files, how to look for help, basics of R philosophy, how to write scripts, what objects are, etc. We will start obtaining our first outputs in R. The aim is to understand the use, potentials, and rationale of R as a platform for different uses.
Tuesday– Classes from 09:00 to 17:00- “Descriptive statistics”
Session 3: Summary statistics (morning)
We will deal with several summary statistics of centrality and dispersion for different types of data, including common and unusual ones. We will understand the theory and the practice of why different types of data have different approaches to summarise them.
Session 4: Graphics (afternoon)
This module will introduce the rationale of using R to obtain graphical outputs of summary statistics. We will also start looking at graphs from statistical inference. We will cover in detail different types of graphs for different types of data and summary statistics. The module on graphics, as all the others, will be a mix of theory and hands-on practical exercises for each approach.
Wednesday –Classes from 09:00 to 17:00 - “Statistical inference”
Session 5 and 6: statistical tests
The whole day will be devoted to theory and practice of commonly used statistical tests, such as correlation, chi square, non-parametric analyses, linear models, etc., understanding their rationale, their use, and their assumptions. After going through the methods that are currently used explaining the reason behind them and how they work, we will apply them to a series of case studies, in order to understand the output that R provides.
Thursday – Classes from 09:00 to 17:00 - “Apply your knowledge to real world”
Session 7: Additional extensions (morning)
In this session we will go through some useful additions that are available in R, such as programming recursive loops, generalised statistical models, and some hints on questions and needs asked by the participants in the first day.
Session 8: Group Tasks (afternoon)
In this session, each attendee will present its research and work project and how R could be used to address some questions in its own daily agenda.
The session is followed by a general discussion about the course.