Introduction to R: A course in the statistical programming environment R

5.- 7. November 2007

Introduction

The Statistics and Decision Analysis Unit will give a three-day hands-on course on the statistical computing package R in the autumn 2007.
The emphasis is on practical applications, with occasional notes about the underlying theory. The course will take place in the computer lab at Research Centre Foulum.
Together with core statistical and graphical procedures, R offers a high-level programming interface which forms a statistical programming environment that makes it easy to extend the functionality of R. This means that it is comparatively easy to implement cutting edge statistical methods in R. Literally hundreds of freely available statistical "packages" of R programs have been offered by researchers throughout the world during the past nearly two decades.
There is a course fee to be paid before course start. See Course fees and payment below.
There are a number of computers in the auditorium for free use. Depending on the number of participants two or more people must share one computer. If you wish, you can bring your own laptop for the practicals. If you do so, you must install the software on your own prior to the course; see installation procedure.
For more information follow the links below.

Course description

R is a freely available implementation of the S language and environment, for statistical computing, and producing graphics similar to the commercial S-PLUS.
This R course is designed for those who want to get started in using R for practical statistical work.
In the course you will learn to write R programs to accomplish typical data-processing tasks, create graphs and fit statistical models.
Topics covered include: an introduction to the R language, reading data, data description and graphics, the general linear models, analysis of variance, non-linear and non-parametric regression, multivariate techniques, the use of R packages and freely available resources in R. We will explore statistical data analysis tools including tools for producing high quality graphics for scientific publications with data sets from various research areas.
In summary, the following topics will be covered:

Prerequisites

You are assumed to be familiar with elementary statistical methodology such as regression models, analysis of variance, hypothesis testing, etc., on a level that is usually offered during courses acquired to pass to get a masters degree.

Additional information

Venue:
Research Centre Foulum, Mødelokale 1 on Monday, 5. 11. to Wednesday, 7. 11. 2007.
As a guest from outside please visit first the information at the main entrance. There you will receive a guest identification card. Afterwards, turn into the direction of the 'Auditorium'. Pass the auditorium and on the left you find the 'Mødelokale 1'.
Accommodation:
A cheap option is Nørresøkollegiet
Teachers:
Ulrich Halekoh (course leader), Erik Jørgensen and Asger Roer Pedersen

Course programme and material

Monday, 5. November 2007

10:00        Welcome and introduction.
10:15 An introductory R session.
10:45 R session 1: Objects: number, vectors, data frames, mathematical and logical operations, indexing
11:15         (Small) Coffee break
11:25 Computer exercises 1: ....
12:00 Lunch
13:00 R session 2: Simple data manipulation, descriptive statistics
13:30 Computer exercises 2: ...
14:15 R session 3: Manipulation of data frames: ordering, reshaping and merging
14:45         Coffee break
15:00 Computer exercises 3: ...
15:45 Winding up the day

Tuesday, 6. November 2007

09:00         Recap from yesterday
09:15         R session 4: Basic R graphics.
09:45         Coffee break
10:00         Computer exercises 4.
10:45         R session 5: Introduction to Trellis graphic (lattice package)
11:15         Computer exercises 5.
12:00         Lunch
13:00         R session 6: Trellis graphics: customizing plots and exporting them.
13:30         Computer exercises 6.
14:15         R session 7: Regression in R: Linear Normal Models, and Analysis of Variance.
14:45         Coffee break
15:00         Computer exercises 7.
15:45         Winding up the day

Wednesday, 7. November 2007

09:00         Recap from yesterday
09:15         R session 8: Regression Model: Hypothesis testing and model checking.
09:45         Coffee break
10:00         Computer exercises 8.
10:45         R session 9: Writing functions in R.
11:15         Computer exercises 9.
12:00         Lunch
13:00         R session 10: Data in and output (for importing data from SAS look at the blog of our research group) R output to Word
13:30         Computer exercises 10.
14:15         R session 11: Further aspects of R: R community and further R packages, keeping R up-to date, GUIs
14:45         Coffee break and course evaluation.

Course material

The complete course material will be provided as lecture notes on the course day.
You find the material for the single days at:
Day 1
Day 2
Day 3
Solutions for most of the practicals contain the necessary R code.

Literature

Course Literature

The main literature used in the course is the "The R Guide" by Jason Owen (PDF). This will, if needed, be supplemented by additional course material handed out during the lectures.

Textbooks on R

There are several books about doing statistical analysis in R. These three are highly recommended.
Further choices for textbooks on R is given in the following comprehensive but not exhaustive list.

Other free information on R

Supplementary information on R can be found at the internet several places:

Installation of R

A short description of how to install R is found at How to install R.
The built-in editor of R will be used during the course. The usability of this editor covers what are needed during the course. The limit time of the course do not permit us to give instructions and help in installing and using other editors mentioned on John Fox's homepage.

Number of participants

There is still place for 4 participants (at the 12. October, 16:00).

Registration

To register, go to the registration form.

Course fees and payment

The fees for the course are:
Employees, PhD and master students of Aarhus University

        Others
Early registration (not later than 30 September 2007) 2700 DKK 5400 DKK
Late registration (not later than 29 October 2007) 3700 DKK 7400 DKK
Payment for participation to the R course must be transferred to our bank account as follows
 
Jyske Bank
DK-1780 Copenhagen V
Denmark
Account no. 8109 1017350
IBAN no: DK 2181090001017350
SWIFT: JYBADKKK

The holder of the account: The Faculty of Agricultural Sciences, University of Aarhus.
The full amount must be made in DKK (Danish kroner). Please observe that we can not accept any reductions for bank charges associated with the transfer. All transfers must be marked with ''Introduction to R - autumn 2007" and the full name of the participant. Unfortunately, we cannot accept bank cheques or euro cheque.
Payment must be received by the organizer no later than 4 days after the registration deadline (e.g. 4. October for early registration and 2. November for late registration). We will confirm your registration when we receive your payment.


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On 18 Nov 2007, 20:39.