How to use this book¶
The shape of every chapter¶
Each of the 40 chapters (8 per grade) follows the same pattern, so you always know where you are:
| Part of the chapter | What it is for |
|---|---|
| Header | track (A no-code / B code), tools, number of lessons, datasets used |
| Big idea | the one sentence to remember |
| What you will be able to do | "I can…" goals — use them to check yourself at the end |
| Words to know | key terms, with Nepali where established (full list in Appendix B) |
| Before you start | what you need from earlier chapters |
| Lessons (2–5) | each = one class period of 40–45 minutes |
| ↳ Hook | a local question to think about — predict before reading on |
| ↳ Explanation | the idea, worked examples, code where relevant |
| ↳ Activity | what to do, step by step (paper and computer versions) |
| ↳ Common mistakes | what most people get wrong |
| ↳ Check | three quick questions |
| ↳ Reflect | "What surprised me? Who or what is missing from this data?" |
| Unit summary | the key points on one screen |
| Practice exercises | ★ recall · ★★ apply · ★★★ think deeper |
| Exercises with real data | using free datasets (codes RD-01 … RD-20, Appendix A) with an offline fallback |
| Unit project | a small investigation following the PPDAC cycle |
| Going further | free resources for the curious |
If you are a student learning on your own¶
- Go in order. Grades build on each other; each chapter's Before you start tells you what you need.
- Predict before you read. Every hook asks a question. Write your guess down. Being wrong first is how you learn.
- Do, don't just read. Work through every worked example yourself — with a pencil for Grade 8, with the computer from Grade 9. Type the code; don't copy and paste it.
- Do the Check questions without looking back. Then check. This "retrieval practice" is one of the most powerful study methods known (see After Grade 12: how to study).
- Do at least the ★ and ★★ exercises. Answers to every ★ exercise are in Appendix G (student edition); the teacher edition has answers to all exercises. With a friend, swap and check each other's work.
- Do the real-data exercises whenever you have internet; they turn practice into real discoveries about Nepal.
- Do the unit project. Projects are where you put the pieces together. Keep them in a folder: by Grade 12 you will have a portfolio.
- Use AI assistants as tutors, not as answer machines (Grade 10 Unit 6): ask for explanations and hints, disclose what you used, and make sure you could explain everything yourself.
A realistic self-study pace is one lesson per day or one chapter per week.
If you are a teacher¶
- Read Part: Teaching data-science foundations, at least chapters 1 (why and what), 4 (a good lesson) and 7 (low-resource classrooms).
- Choose your track:
- Track A (no-code) — paper, calculator, spreadsheet or CODAP. Fits inside compulsory Maths, Science, Social Studies or Health. Grade 8 is entirely Track A; many Grade 9–12 lessons have a Track A version.
- Track B (code) — SQL and Python (JupyterLite in the browser works offline). Fits optional Computer Science, ICT clubs and Grades 11–12.
- Use the teacher guide for each unit (teacher edition): timings, materials, misconceptions, differentiation, answer keys for Checks, practice and real-data exercises.
- Pace realistically. Each unit = 3–5 lessons + a project (about 2 periods). A full grade = 8 units ≈ 40 periods, one period a week for a year, or two a week for a term. See Planning a year in the teaching part for options when you have less time.
- Adapt freely. Change examples to your district, swap datasets, translate. The licence allows it; please share improvements.
Tracks and grades at a glance¶
| Grade | Theme | Tools | Track |
|---|---|---|---|
| 8 | Data detectives | paper, calculator, CODAP | A |
| 9 | Data wranglers | spreadsheet, SQL, first Python, pandas | A/B |
| 10 | Data analysts | Python (pandas, matplotlib), Streamlit | B (Unit 6: A) |
| 11 | Data scientists I | Python, numpy, SQL, Git | B |
| 12 | Data scientists II | Python, scikit-learn | B (Unit 7: A/B) |
Synthetic and real data¶
Practice tables in the datasets/ folder are synthetic: invented numbers, shaped like real Nepali data, with
fictional district names such as Hill-07. They let every lesson run offline and let the book show exact answers. Never
quote them as facts about Nepal. Real data appear in the Exercises with real data, downloaded from the publisher (see
Appendix A), and in the worked examples where a publisher's licence allows it (for example, child mortality from Our
World in Data in Grade 8 Unit 4).
Symbols and conventions¶
- ★ / ★★ / ★★★ — exercise difficulty.
- RD-05 — real dataset number 5 in Appendix A.
code— something to type, a file name or a column name.- Code blocks in chapters are tested automatically: they run as printed on the shipped synthetic data.
- Dates are written in ISO form (2026-10-11) unless a Bikram Sambat (BS) date is meant, which is marked "BS".
Two editions¶
- Student edition — everything above, without the teacher guides, plus answers to the ★ exercises (Appendix G).
- Teacher edition — adds each unit's teacher guide (timings, misconceptions, answers to all exercises and notes on the real-data exercises) and the teaching handbook.