Statistics for Life Scientists

Overview

Statistics are an integral aspect of scientific research, particularly for the life sciences which rely heavily on quantitative methodologies. This course is designed to provide researchers in the life sciences with experience in the application of basic statistical analysis techniques to a variety of biological problems.

Attendees will work through short tutorials on the topics discussed in the class. These practical exercises will be implemented in the widely used "R" language and environment for statistical computing and graphics.

Topics covered during the course include:

• What is a probability? (theoretical and historical perspectives)
• Reproducible research
• Data summarization
• Common distributions
• Hypothesis tests (and which [not] to use)
• Unsupervised learning (clustering, PCA, applications to batch effects)
• Supervised learning (linear models, logistic regression, generalized linear models, random forest)

Audience

This course is intended for life scientists from all levels and disciplines who are not experts in statistics. Although participants are not required to have a strong background in statistics, they must be comfortable with the R environment and be able to read, understand and write R commands before attending this course.

Learning objectives

At the end of the course, participants should be comfortable exploring their data towards choosing the most appropriate model(s) for their analysis, implementing the model(s) and exploring the parameter space, and meaningfully interpreting the results.

Prerequisites

Knowledge / competencies: Completion of a basic/introductory course on R is the minimum requirement, however completion of an intermediate or advanced R course is recommended. Participants must be comfortable with the R environment and be able to read, understand and write R commands before attending this course.

Technical: Participants must bring a a Wi-Fi enabled laptop with R and RStudio installed. More information about the packages needed will be provided before the course. Participants will be asked to submit data confirming they have a suitable R environment enabled for the course.

Location & Time

University of Basel, Kollegienhaus, Seminarraum 103, Petersgraben 50, 4051 Basel

Application

The registration fees for academics are 240 CHF. This includes course content material and coffee breaks. Participants from non-academic institutions should contact us before application.

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.

Additional information

Coordination: Geoffrey Fucile

You are welcome to register to the SIB courses mailing-list to be informed when the applications for this course will be open, of all future courses and workshops, as well as all important deadlines using the form here.

For more information, please contact training@sib.swiss.