• Biostatistics
  • Goal of this WebBook
  • Academic Integrity
  • Zoom links
  • Installing R & RStudio
  • Lecture 1: Introduction
  • Tutorial 1: The R environment
  • Lecture 2: Statistical Hypotheses Testing
  • Tutorial 2: Statistical Hypothesis Testing
  • Lecture 3: Stat. Hyp. Testing - part 2
  • Reference Search
  • Lecture 4: Estimators and Factorial ANOVA
  • Lecture 5: Factorial ANOVA part 2
  • Tutorial 3: Factorial ANOVA
  • Lecture 6: Post-Hoc Tests
  • Lecture 7: Non-parametric tests
  • Tutorial 4: Multiple Testing
  • Lecture 8: Heteroscedasticity
  • Lecture 9: ANCOVA
  • Tutorial 5: Rank-transformation and Heteroscedasticity
  • Lecture 10: Types of Sum of Squares
  • Lecture 11: Multiple regression
  • Tutorial 6: ANCOVA
  • Lecture 12: Multiple regression part 2
  • Lecture 13: Multiple regression part 3
  • Tutorial 7: Multiple regression in practice
  • Lecture 14: A new look into Heteroscedasticity
  • Tutorial 8: Heteroscedasticity and GLMs
  • Lecture 15: Mixed models part 1
  • Lecture 16: Mixed models part 2
  • Tutorial 9: Mixed models - part 1
  • Lecture 17: Mixed models part 3
  • Lecture 18: Machine Learning - K-means
  • Tutorial 10: Mixed models - part 2
  • Lecture 19: Machine Learning - trees
  • Lecture 20: PCA
  • Tutorial 11: Machine Learning
  • Lecture 21: Multivariate Response Models
  • Tutorial 12: PCA and RDA
  • Published with bookdown

Advanced Statistics for Biological Sciences - BIOL422 & BIOL680 - 2025

Zoom links

This is legacy from the 2022 version of the course and doesn’t apply to 2025.