Description

Book Synopsis
Much training in quantitative social science focuses on data analysis and fails to equip researchers with the skills to prepare the data required for this. This book is a comprehensive introduction to simple and advanced tools for data management, drawing on established concepts and techniques from computer science.

Table of Contents
Part I. Introduction: 1. Motivation; 2. Gearing up; 3. Data = content + structure; Part II. Data in Files: 4. Storing data in files; 5. Managing data in spreadsheets; 6. Basic data management in R; 7. R and the tidyverse; Part III. Data in Databases: 8. Introduction to relational databases; 9. Relational databases and multiple tables; 10. Database fine-tuning; Part IV. Special Types of Data: 11. Spatial data; 12. Text data; 13. Network data; Part V. Conclusion: 14. Best practices in data management.

Data Management for Social Scientists

    Product form

    £25.99

    Includes FREE delivery

    Order before 4pm today for delivery by Sat 25 Jul 2026.

    A Paperback by Nils B. Weidmann

    1 in stock

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of Data Management for Social Scientists by Nils B. Weidmann

      Publisher: Cambridge University Press
      Publication Date: Publication Date: 3/9/2023 12:00:00 AM
      ISBN13: 9781108964784, 978-1108964784
      ISBN10: 1108964788
      Also in:
      Social research and statistics

      Description

      Book Synopsis
      Much training in quantitative social science focuses on data analysis and fails to equip researchers with the skills to prepare the data required for this. This book is a comprehensive introduction to simple and advanced tools for data management, drawing on established concepts and techniques from computer science.

      Table of Contents
      Part I. Introduction: 1. Motivation; 2. Gearing up; 3. Data = content + structure; Part II. Data in Files: 4. Storing data in files; 5. Managing data in spreadsheets; 6. Basic data management in R; 7. R and the tidyverse; Part III. Data in Databases: 8. Introduction to relational databases; 9. Relational databases and multiple tables; 10. Database fine-tuning; Part IV. Special Types of Data: 11. Spatial data; 12. Text data; 13. Network data; Part V. Conclusion: 14. Best practices in data management.

      Recently viewed products

      © 2026 Book Curl

        • American Express
        • Apple Pay
        • Diners Club
        • Discover
        • Google Pay
        • Maestro
        • Mastercard
        • PayPal
        • Shop Pay
        • Union Pay
        • Visa

        Login

        Forgot your password?

        Don't have an account yet?
        Create account