Data Science tools for students of the Life Sciences

Graduiertenakademie
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The course intends to provide students in life sciences expertise and adequate tools to identify data that are relevant for a research question, and analyze them in a meaningful way. For a reproducible environment, the course will utilize the open-source language package of R on Jupyterhub. Major emphasis of the course will be on data retrieval, data management, and data handling in R.

Students will learn how to handle different data formats, and how to employ the appropriate tools to read these data into the R programming environment.
Students will learn how to perform exploratory data analysis, with an emphasis on data visualization based on the ”tidyverse” collection of packages in R.
Students will be introduced to basic statistics, and how these can be applied in R. Starting with the basic concepts of statistics (distributions, means, variance, hypothesis testing, regression analysis), students will be introduced to the deployment of general linear models (glm). Particular emphasis will be laid on the underlying assumptions of the statistical models, and how to check whether these assumptions are met (residual analysis). Further concepts taught will be the use of model selection based on information criteria (AIC), multivariate approaches, generalized models (poisson, binomial), generalized additive models and models with random effects ...

Instructor: Dr. Alexander Scheuerlein
Date: 09.09.2024 – 27.09.2024, 9:00 – 15:00
Place: Seminarraum 0.08, Rechenzentrum, Felix-Hausdorff-Straße 18, 17489 Greifswald
Participants: max. 20

Registration
HIS ID
Moodle

Contact
Graduiertenakademie 
Domstraße 11, Eingang 4, Raum 3.24, 17489 Greifswald
Telefon +49 3834 420 1618
graduiertenakademieuni-greifswaldde

 

Organization

  • Graduiertenakademie der Universität Greifswald

Location

  • Universitätsrechenzentrum
    Felix-Hausdorff-Straße 18
    17489 Greifswald