Basic statistics theory
Basic statistics theory
General context
This course introduces the core principles of statistics for the analysis of life sciences data. It is highly recommended for participants planning to take the follow-up course "Basic statistics in R, especially those without prior statistical knowledge.
Unlike tool-specific trainings that focus on implementation, this course explains the underlying concepts: why specific tests are chosen, how to select the most appropriate visualization, and how to interpret results correctly. Through an e-learning format, you learn at your own pace and explore essential topics, including how to describe and visualize data, select the right statistical tests, apply best practices for reporting, and improve the power of your analyses with practical tips and real-life examples.
- Explain fundamental statistical concepts for life sciences data analysis
- Select the appropriate statistical test for different types of data
- Choose effective visualizations for presenting data
- Interpret and critically evaluate the results of basic statistical analyses
Self-paced e-learning course combining theoretical explanations and quizzes.
People who want to follow: 'Basic statistics in R' or 'Basic statistics in Prism' and who have no statistics background.
None
This course is part of multiple learning paths.
Trainers
Janick Mathys
Janick tries to help VIB scientists analyze their data by offering bioinformatics training and support. Next to organizing trainings, creating e-learning courses and teaching statistics, R, Python, Linux, HPC, bulk and single cell RNA-Seq analysis, she consults scientists and develops pipelines for omics analyses. Before joining VIB, she worked as a post-doc at KULeuven, doing research on transcriptomics and transcription regulation. She coordinated the Master of Bioinformatics program of KULeuven and taught the course on Biological Databases.