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docs/chapters/README.md

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+# Chapter Notes (R ↔ Python)
+
+This folder holds one DOCX (and optionally a PDF export) per chapter, built from the template:
+**PyStatsV1-Chapter-Template.docx**.
+
+## How to create a new chapter notes file
+
+1) **Copy the template**
+   - Copy `PyStatsV1-Chapter-Template.docx` to `docs/chapters/ChXX_<short-topic>_Notes.docx`
+   - Examples:
+     - `Ch07_SimpleLinearRegression_Notes.docx`
+     - `Ch08_Inference_SLR_Notes.docx`
+     - `Ch09_MultipleLinearRegression_Notes.docx`
+
+2) **Fill the sections**
+   - **Goal & Outputs**: what the chapter computes/plots in R & Python
+   - **Dataset & Reproducibility**:
+     - list input files (e.g., `data/autompg.csv`)
+     - record seeds and exact commands to run both R and Python
+   - **R Approach (from textbook)**: formulas + key functions (`lm`, `confint`, `predict`, etc.)
+   - **Python Approach (mirror)**: pandas/statsmodels/scipy/matplotlib equivalents
+   - **Side-by-Side Commands**: keep short, runnable snippets
+   - **Diagnostics & Checks**: reference images saved by scripts (see below)
+   - **Pitfalls & Equivalences**: factors vs categoricals, NA handling, formula differences, defaults
+   - **Attribution & License Notes**: see licensing section below
+
+3) **Screenshots & figures**
+   - Save images generated by scripts under `outputs/`, and reference them in the DOCX.
+   - If you add static images for the notes themselves, place them here:
+     - `docs/chapters/img/ChXX/` (create as needed)
+     - Example: `docs/chapters/img/Ch07/residuals.png`
+
+4) **Recommended naming**
+   - DOCX: `ChXX_<Topic>_Notes.docx`
+   - (Optional) PDF: `ChXX_<Topic>_Notes.pdf`
+   - Keep topic names short and clear.
+
+## Reproducibility block (copy/paste)
+
+**Windows (Git Bash / PowerShell)**
+```
+python -m venv .venv
+source .venv/Scripts/activate 2>/dev/null || .venv\Scripts\Activate.ps1
+pip install -r requirements.txt
+python scripts/chXX_<topic>.py --save-outputs
+```
+
+**macOS / Linux**
+```
+python -m venv .venv && source .venv/bin/activate
+pip install -r requirements.txt
+python scripts/chXX_<topic>.py --save-outputs
+```
+
+If the chapter has an R counterpart, also include:
+```
+Rscript chXX_<topic>.R
+```
+
+## Licensing & attribution
+
+- **Book content**: The source textbook *Applied Statistics with R (STAT 420)* is **CC BY-NC-SA 4.0**.
+  Do **not** copy large verbatim passages. When quoting or closely paraphrasing, provide attribution and keep it non-commercial and share-alike compatible.
+- **This repo’s Python code**: MIT (see `LICENSE`).
+- **These notes**: Paraphrase and attribute. If you include longer excerpts, ensure they comply with **CC BY-NC-SA 4.0**.
+
+## Chapter checklist
+
+- [ ] R command(s) listed and runnable
+- [ ] Python command(s) listed and runnable
+- [ ] Inputs named (file paths, seeds)
+- [ ] Outputs referenced (plots/tables)
+- [ ] Key equivalences documented (R ↔ Python)
+- [ ] Diagnostics summarized (residuals, QQ, leverage if relevant)
+- [ ] Attribution present; licensing constraints respected