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TGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAACGGTCCTTAAGCTGTATTGCACCATATGACG
GATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTTCGGTCCTTAAGCTGTATTCCTTAACAACGGTCCTTAAGG
ATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAAGTAC
TGCCTCGGTCCTTAAGCTGTATTGCACCATATGACGGATGCCGGAATTGGCACATAACAACGGTCCTTAAGCTGTATTGCACCATATGACG
GATGCCGGAATTGGCACATAACAAGTACTGCCTCGGTCCTTAAGCTGTATTTCGGTCCTTAAGCTGTATTCCTTAACAACGGTCCTTAAGG
Advanced Statistics: Statistical Modeling
03 June 2016
For-profit: 0 CHF
No future instance of this course is planned yet
Overview
In classical linear modeling we are assuming that the response variable (Y) is normally distributed, however for certain type of data, like count data or presence/absence data, this is not the case. In this course, we will thus see more advanced statistical models and techniques to provide you the necessary set of tools that will enable you to analyze different types of (biological) data.
The course will be centered on "statistical modeling" applied to biological problems. Topics addressed during this course include advanced linear models, mixed models, generalized linear models, survival analysis. The emphasis will be put on concrete applications in biology.
Audience
This course is intended for life scientists who already have some basic knowledge of statistics and the programming language "R".
Learning objectives
At the end of this course, participants are expected to be able to:
- understand statistical modeling
- understand the specificities of the different models
- identify the appropriate model to analyze a dataset
- fit the desired model using R
Prerequisites
Knowledge / competencies:
The course is intended to people already familiar with basic statistics and R. In particular people who have already followed the course "introduction to statistics for biologists". Participants must be comfortable with topics such as hypothesis testing, linear models, regression and must have a prior knowledge of the "R" language and environment for statistical computing and graphics.
Technical:
Participants must bring a laptop with at least 4 Gb of RAM and the "R" software installed. More information about the packages needed will be provided before the course.
Application
The course is full.
The registration fees for academics are 200 CHF. This includes course content material, coffee breaks, and a social dinner. Participants from non-academic institutions should contact us before application.
Deadline for registration and free-of-charge cancellation is set to June 3, 2016. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to this and other general conditions, available here.
You will be informed by email of your registration confirmation. Upon reception of the confirmation email, participants will be asked to confirm attendance by paying the fees within 5 days.
Location
University of Lausanne, Génopode Building, room 2020 (UNIL sorge M1 line stop)
Additional information
Coordination: Diana Marek
You are welcome to register to the SIB courses mailing-list to be informed of all future courses and workshops, as well as all important deadlines using the form here.
For more information, please contact training@sib.swiss.