Introduction to R
Any researcher is welcome to follow this course. No previous
knowledge of R is required.
Medical Statistics in R
In this course an introduction to basic statistical methods useful
for biomedical data analysis will be given. It is for any
professional involved in research that requires using statistical
During the course we will alternate between lectures and
practicals, allowing for plenty of interaction and illustration
with examples of practical interest.
We will use R (http://www.r-project.org) for
all practicals. Participants with no experience in R are strongly
advised to follow an introductory R course prior to following this
course (see pre-requisites for suggestions).
Link to pdf or book
What is R?
R is an open-source,
free environment for statistical computing and graphics. It
provides a large repository of statistical analysis methods, both
classic and new. However, R has a steep learning curve, due partly
to its using a command-line type of user interface, rather than the
usual pull-down menus. This 3-day course aims at helping
researchers climb this curve, enabling them to perform basic data
analysis and graphic displays at the end of the course, as well as
giving a platform from which they can deepen their R knowledge
later on if necessary.
Goals & Topics
After the course you will be able to:
- understand and write simple R programs
- use R to perform basic statistical analyses of your own data
- generate analysis reports from your own data in html or pdf
formats, using RMarkdown
We will cover the following topics:
- R expressions and formula objects
- R data objects (vectors (arrays), data frames (tables), lists,
matrices) creation and usage
- R functions for descriptive statistics and linear model
- installing additional libraries
- histograms, scatter plots, boxplots (in pure R )
Renee X. de Menezes