3 materials found

Contributors:

PSLS22 Practical Statistics for the Life Sciences

This intermediate level course is one of our Foundations courses. It covers essential statistical concepts and methods for extracting insights from empirical data in the life sciences. The course positions applied statistics, starting from important aspects of experimental design and data...

PSLS22 Practical Statistics for the Life Sciences http://tess.elixir-uk.org/materials/psls22-practical-statistics-for-the-life-sciences This intermediate level course is one of our Foundations courses. It covers essential statistical concepts and methods for extracting insights from empirical data in the life sciences. The course positions applied statistics, starting from important aspects of experimental design and data exploration. We then move into statistical modeling and data analysis. We will focus on the link between linear regression and analysis of variance. Together, these methods contribute to the study of General Linear Models. The course also introduces the basics of non-parametric testing, and addresses categorical data analysis and logistic regression. Lieven Clement Milan Malfait Jeroen Gilis Graduate students All postgraduates
PSLS20 - Practical Statistics for the Life Sciences (2020)

Training material that covers essential statistical concepts and methods for extracting insights from empirical data in the life sciences.

Keywords: Statistics, General Linear Models

Resource type: Documentation, Exercise, Handout, Scripts

PSLS20 - Practical Statistics for the Life Sciences (2020) http://tess.elixir-uk.org/materials/psls20-practical-statistics-for-the-life-sciences-2020 Training material that covers essential statistical concepts and methods for extracting insights from empirical data in the life sciences. Lieven Clement Jeroen Gilis Statistics, General Linear Models Academia/ Research Institution Industry Healthcare Non-Profit Organisation
Introductory image processing on biological images using python.

A jupyter notebook python practical designed to give students a introduction to opening and processing image files derived from biological samples.

Resource type: Jupyter notebook, PDF

Introductory image processing on biological images using python. http://tess.elixir-uk.org/materials/introductory-image-processing-on-biological-images-using-python A jupyter notebook python practical designed to give students a introduction to opening and processing image files derived from biological samples. Anatole Chessel Volker Baecker Bioimage Analysts Image Analysts Computer Vision scientists bioinformaticians computational scientists Biophysicists Biologists Microscopists Python for Biologists PhD students