How to use this book

We begin with a short orientation in which we explain the chapter template, the cross-references to sibling volumes, and the conventions used throughout the book. The template is the same as the one in the SCAI-advanced and applied-genai sister volumes.

Chapter template

Every content chapter shall follow the same nine-section structure:

  1. Learning objectives. A bulleted list of the capabilities the reader should have after working through the chapter.
  2. Orientation. Two to four paragraphs of prose framing, in which we set out what the chapter is, why it matters, and how it relates to adjacent chapters and to the sister volumes.
  3. The statistician’s contribution. A front-loaded section in which we articulate the judgments at the center of the chapter that no large language model can make on the reader’s behalf.
  4. Content sections. The chapter’s substantive material, broken into sections with descriptive headings. Collapsible Check your understanding callouts appear at natural pauses.
  5. Worked example. A concrete worked example, ideally biomedical, that exercises the chapter’s tools end to end.
  6. Collaborating with an LLM on topic. Three prompt patterns paired with what to watch for and how to verify, specific to the chapter’s content.
  7. Principle in use. Three habits that define defensible work in this area.
  8. Exercises. Five exercises ranging from short conceptual checks to extended applied work.
  9. Further reading. Canonical, modern applied, and software-documentation pointers.

The template is identical to the one in the SCAI-advanced and applied-genai sister volumes; the reader who is familiar with those volumes may read this one in the same rhythm.

Conventions

The visual cues used throughout the book are described on the Conventions page. Code blocks default to R; Python and Stan snippets are labeled. LLM prompts are shown in fenced blocks, with the prompt text and the accompanying verification commentary.

Companion repositories and audit trail

The book repository at https://github.com/rgt47/applied-methods contains the following:

  • docs/curriculum-gap-analysis.md, the survey across 24 graduate programs that identified the topical gaps this volume fills.
  • references.bib, the working bibliography.

The audit trail is intentional. Subsequent revisions of the volume shall be informed by tracking how MS-program curricula evolve, and the survey document serves as the benchmark against which we measure that change.