---
title: "Combined demo"
subtitle: "All four extensions on one slidedeck"
code-annotations: select
filters:
  - fragmention
  - cascade
revealjs-plugins:
  - codefrag
  - tabset
---

## Workflow

- []{.fragment fragment-index="1"} Collect and validate the inputs.
- []{.fragment fragment-index="2"} Transform with a small pipeline.
- []{.fragment fragment-index="3"} Summarise and report.

## Pipeline code

```{.r code-line-numbers="|1|2-3|4"}
library(dplyr)                          # <1>
mtcars |>
  filter(cyl == 6) |>                   # <2>
  summarise(mean_mpg = mean(mpg))       # <3>
```

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.

---

- Stable across bootstrap resamples.
- No outliers detected.

## Diagnostics {.smaller}

::: {.panel-tabset}

### Residuals

- Centred around zero.
- No visible trend against fitted values.

### Influence

- Cook's distance below the usual threshold.
- No single point dominates the fit.

### Notes

- Model re-fit on a held-out split.
- Results replicate within tolerance.

:::
