Statistics for Bioinformatics and eScience (StatBI/E)

Course description

Content

The course will take the participants through the following content:

• Standard discrete and continuous distributions, descriptive methods,  Bayes’ theorem, conditioning, independence, and selected probability results.
• Simulation.
• Mean, variance, estimators, two-sample comparisons.
• Maximum likelihood and least squares estimation.
• Standard errors and confidence intervals.
• Bootstrapping.
• Correlation, (generalized) linear and non-linear regression.
• The statistical programming language R and R notebooks.

Recommended academic qualifications

IMPORTANT: This course requires and assumes quantitative/​mathematical prior knowledge equivalent to a MatIntro or equivalent course!

Academic qualifications equivalent to a BSc degree is recommended.