Student Resources
All the resources you need as a student using Data Analysis for Business, Economics, and Policy: slides, datasets, case studies, coding setup, and Q&A support.
Quick links
Start here in 3 steps
This textbook supports independent study with clear explanations, practical advice, coding practice, and exercises.
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Open your chapter: go to the Chapters overview or pick a case study.
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Set up and get the materials: choose Stata, R, or Python follow the setup guides, and download the datasets and scripts from Data & Code — the same files used in the book.
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Practice with exercises: after each chapter, complete the questions and coding tasks to check your understanding and build confidence.
Coding setup
Setup guides: Stata · R · Python
Learning resources (for beginners): Coding for Data Analysis · Python basics · R basics · Stata basics
Data & Code
All data and code are open and reproducible. You will use the same repositories instructors use.
- Case study code (R, Python, Stata): Case studies · GitHub repository
- Datasets: Datasets on OSF · Dataset summaries
See the Data & Code page for details on downloading data, organizing folders, and checking out the GitHub repo.
Student Q&A and support
Use these resources when you have questions or want to check solutions discussed in class.
Found an error or would like to contribute? You can open an issue on GitHub or get in touch with us.
Going deeper (optional)
These are student-friendly extras that also appear on the instructor side. Great if you want to stretch further or explore on your own.
- Why this book · How it is organised
- Additional reading
- Data source ideas
- Advice on learning to code
- Choice of programming language
- Order · Request an examination copy
We deliberately exclude instructor-only materials (editable slide sources, full solutions) from this page. If you need help, use the Q&A pages or contact us.