Combined demo

All four extensions on one slidedeck

Mickaël Canouil, Ph.D.

mickael.canouil.fr

2026-04-20

Workflow

  • Collect and validate the inputs.
  • Transform with a small pipeline.
  • Summarise and report.

Pipeline code

library(dplyr)
mtcars |>
  filter(cyl == 6) |>
  summarise(mean_mpg = mean(mpg))
1
Load dplyr.
2
Keep only six-cylinder cars.
3
Compute the mean mileage.

Results

Summary

  • Mean mileage: 19.7 mpg.
  • Sample size: 7 cars.

Results

Summary

  • Stable across bootstrap resamples.
  • No outliers detected.

Diagnostics

  • Centred around zero.
  • No visible trend against fitted values.
  • Cook’s distance below the usual threshold.
  • No single point dominates the fit.
  • Model re-fit on a held-out split.
  • Results replicate within tolerance.