7: Quarto & Reproducibility

Content for Monday, April 20, 2026

Before class

📖 Reading:

During class

We’ll cover:

  • What is literate programming? Code + narrative in one document
  • Why reproducibility matters
  • Quarto basics: YAML header, Markdown text, code chunks
  • Code chunk options: echo, eval, include, message, warning
  • Figure options: fig-width, fig-height, fig-cap
  • Inline code — embedding results in text (never hard-code statistics!)
  • Output formats: HTML, PDF, Word
  • Tables with knitr::kable()
TipAssignment 3 is assigned today

Assignment 3: Tidying, Import & Quarto — due Sunday, April 26 at 11:59 PM.

Slides

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After class

✅ Practice:

  1. Create a new Quarto document (.qmd). Add a title, your name, and today’s date in the YAML header
  2. Write a short introduction in Markdown — use headers, bold, italic, and a bulleted list
  3. Add a code chunk that loads a dataset and creates a plot. Try #| echo: false to hide the code
  4. Use inline code to report a summary statistic in a sentence (e.g., “The mean age was `r knitr::inline_expr("mean(data$age)")`”)
  5. Render your document to HTML. Then try PDF (you may need to install tinytex)
NoteThe golden rule of reproducibility

Never hard-code a number in your text. If your data changes, your text should update automatically.

Instead of: > “The mean score was 4.2.”

Write: > “The mean score was `r knitr::inline_expr("round(mean(data$score, na.rm = TRUE), 1)")`.”

This way, if you add more data or fix an error, everything stays in sync.

Useful chunk options

#| label: fig-results
#| echo: false
#| fig-cap: "Mean anxiety scores by condition"
#| fig-width: 8
#| fig-height: 5

ggplot(data, aes(x = condition, y = anxiety)) +
  stat_summary(fun = mean, geom = "bar") +
  stat_summary(fun.data = mean_se, geom = "errorbar", width = 0.2)