Statistical models in biology
All models are wrong, but some models are useful.
— George Box, British statistician
These courses address the principles of data analysis in biology. You may "bring your own data" to some of them.
Foundational courses
Start with these lectures to gain a solid understanding of the basics of statistical analysis in a biological context.
Advanced courses
"Machine Learning" !
"Neural Networks" !!
"AI" !!!
Hype and buzzwords come and go. At the end, statistical models remain that map predictors ("independent variables") to responses ("dependent variables").
We offer in-depth courses that teach you statistical model building in a biological context.
| Method family | Predictors | Responses | Courses |
|---|---|---|---|
| ANOVA | Categorical | Quantitative | ANOVA with R |
| Regression | Quantitative | Quantitative | Linear regression with R |
| Nonlinear regression with R | |||
| Generalized linear models with R | |||
| Classification | Quantitative | Categorical | Clustering and Classification with Python |
Obsolete courses
These courses are not offered any longer.