Monday – Classes from 2 to 8 pm Berlin time - “Introduction to R”
Session 1: Introduction
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
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 2 to 8 pm Berlin time-
“Descriptive statistics”
Session 3: Summary statistics
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
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 2 to 8 pm Berlin time -
“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 2 to 8 pm Berlin time-
“Apply your knowledge to real world”
Session 7: Additional extensions
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
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.