Statistics in Action with R
  • Hypothesis testing
    • documentation
    • Single comparisons
    • Multiple comparisons
    • Shiny apps
    • Hypothesis testing for the mean
    • Law of large numbers (LLN)
    • Central limit theorem (CLT)
    • exercices
  • Regression models
    • documentation
    • Polynomial regression: an example
    • Polynomial regression: going into details
    • Nonlinear regression
    • Maximum likelihood estimation in a Gaussian regression model
    • Some residual error models
    • exercices
    • Shiny apps
    • Linear regression
    • Bayesian fitting of longitudinal data
  • PK modelling
    • documentation
    • Introduction to pharmacokinetics modelling
    • The ADME process
    • movie
    • Introduction to PK modelling
    • Shiny apps
    • Build your PK model
    • Comparing different absorption processes
    • Combining oral and iv administrations
  • Mixed effects models
    • documentation
    • linear mixed effects models
    • EM algorithm for linear mixed effects models
    • nonlinear mixed effects models
    • movie
    • Introduction to the population approach
    • exercices
    • Shiny apps
    • Linear mixed effects model (growth curve)
    • Nonlinear mixed effects model (growth curve)
    • Nonlinear mixed effects model (PK modelling)
  • Mixture models
    • documentation
    • exercices
  • Signal & Image
    • documentation
    • Detection of changes in a signal
    • Bayesian restoration of images
    • exercices
    • Detection of changes
    • Restoration of images
    • Shiny apps
    • Detection of multiple change points in the mean and/or variance
  • Ressour