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ResearchPhD courses

Advanced Statistics using R


Prof. Ido Pen (Theoretical Biology, Groningen Institute for Evolutionary Life Sciences, RUG)

Course lecturers

Prof. Ido Pen (Theoretical Biology, Groningen Institute for Evolutionary Life Sciences, RUG)

Dr. Sander van Doorn (Evolutionary Systems Biology, Groningen Institute for Evolutionary Life Sciences, RUG)

Aim of the course

Learn how to master the art of advanced data analysis and graphical presentation, using the shareware program R.

At the end of the course, the student is able to:

1. The student can translate specific combinations of experimental design and data into appropriate statistical models.
2. The student can program and analyze statistical models in R.
3. The student can summarize statistical analyses with appropriate tables and graphs.
4. The student can draw justified inferences and conclusions from statistical analyses.
5. The student can describe statistical methods, analyses and conclusions in a format suitable for publication.

Contents & Structure

This course offers an introduction to R and offers a review of basic statistics. Further topics that will be: general linear models (ANOVA, ANCOVA, multiple regression); generalized least squares; mixed models; generalized linear models; generalized linear mixed models; Bayesian analysis and MCMC; animal models; multivariate analysis. During the last week of the course you are expected to analyse your own data set and present the results.

This course teaches advanced statistical analysis almost from the ground up. The only requirement is some familiarity with basic statistical concepts and methods, such as taught in most introductory statistics courses. Some experience with R is useful but not crucial. During
the first three days, basic methods and R will be reviewed to refresh your memory. During the next two weeks, cutting-edge techniques such as GLMMs, power analyses and Bayesian MCMC models will discussed and practiced. Each day will start with a review of the exercises of the previous day, followed by lectures and new computer labs. Mathematics will be kept to
a minimum, and in addition to developing analytical skills, the course also puts much emphasis on producing effective and great-looking graphs (mostly using the ggplot2 package).
The last week of the course will be dedicated to analyzing your own data, unleashing the newly learned techniques. If you have no data yet, alternative suitable data will be found elsewhere or simply created de novo with simulation models. Your methods, results and conclusions will be documented in a report which will be graded.

General Information
Required knowledge & preparation Some knowledge of biostatistical analysis.
Course material Relevant literature will be provided during the course.
Course credits 5 ECTS when following the entire course.
Location Linnaeusborg, Zernike Campus, Groningen
Duration & date 5 weeks, starting 27 May until 29 June 2019. There are usually 4 course days per week, Monday to Tuesday, Thursday - Friday from 9 - 17 hrs.
Costs Master level students participate in the course at no cost. PhD level students of GELIFES will be charged a course fee of € 275,- to cover teaching costs. The course fee for external participants is € 425,-. You will receive an invoice for this fee after your registration has been approved.
Participants There is currently no set limit to the number of participants.
Information Course content: Ido Pen (Theoretical Biologie, Linnaeusborg 5172.0574, Phone: 8083).
Practical information: Corine Eising (RSEE course coordinator, Linnaeusborg 5173.0504, Phone: 9140).
Registration Master level students should register via the appropriate channels (Ocasys, Progress) for this course. PhD level students wishing to participate in this course should contact the course teacher, Ido Pen first, with a cc to Corine Eising.
Registration for this course is now open. PhD students, please take note of the RSEE cancellation policy!
Last modified:17 June 2019 5.04 p.m.