851402 Instructional course IVD - applied statistics for life sciences
This page is available under these URLs:
- Exercise course
- Semester hours
- Lecturer (assistant)
- Leisch, Friedrich , Scharl-Hirsch, Theresa
- Offered in
- Wintersemester 2022/23
- Languages of instruction
This course will refresh the principles of statistical data analysis.
Topics covered include
1. Scales for variables (categorical, numerical), corresponding distributions,
2. Visualization of multivariate data sets
3. Statistical inference – confidence intervals, parametric &
non-parametric tests in the one-, two- and many-sample situations
4. Simple and multiple linear regression and their extensions (categorical predictors,
polynomial regression, interaction terms), model diagnostics, variable selection
5. Logistic regression for binary target variables
6. More advanced methods depending on the needs of course participants
We will deal with examples from the fields of life sciences/biostatistics/biotechnology throughout this course using the statistical environment R.
- Previous knowledge expected
Master degree enabling to enroll in a BOKU PhD program.
- Objective (expected results of study and acquired competences)
Participants of the course
• recognize the need for a statistical treatment or analysis of their
data analytic problems,
• can translate research questions into statistical hypotheses,
• choose the correct method(s) to solve these problems and know
how to check their assumptions,
• can assess the quality of a fitted model,
• use models to investigate associations between variables or
predict target variables for new inputs,
• perform these steps using the statistical software environment R,
• and are able to present the results in talks and scientific articles.
You can find more details like the schedule or information about exams on the course-page in BOKUonline.