R for Non-Programmers

1. Auflage 2025
ISBN: 978-1-032-78014-6
Verlag: CRC Press

Buch, Englisch, 408 Seiten, Format (B × H): 156 mm x 234 mm

Unlock the Power of Data Analysis with R
Whether you are a researcher, student, or professional new to programming, this book provides a step-by-step guide to mastering R for quantitative and mixed-methods analysis. Designed for those who still need to gain programming experience or wish to learn a new one, it demystifies data analysis, helping you tackle challenges from data wrangling to statistical modelling. Packed with practical examples, engaging explanations, and real-world applications, this book equips you with the tools to analyse data confidently, identify trends, and uncover meaningful insights.

Transform Your Approach to Research
Through clear instructions and hands-on exercises, you will learn to prepare datasets, explore patterns with descriptive statistics, and create impactful visualisations. You will also gain confidence in performing statistical tests such as comparing groups, and building predictive models using regression techniques. This book provides strategies and tools to streamline your workflow, whether handling large datasets, managing missing data, or conducting mixed-methods research.
Each chapter builds your expertise incrementally, supported by accessible examples and interactive online training. The accompanying training modules, available through the book’s companion package, offer engaging exercises and extended examples to reinforce learning. These features enable you to practise skills and retain knowledge more effectively.
This book, which strongly focuses on reproducible research, is an indispensable guide for anyone looking to enhance their analytical toolkit and unlock R's full potential for data analysis and statistical modelling.

Zielgruppe

General, Postgraduate, Professional Reference, and Undergraduate Core

Autoren/Hrsg.

Dauber, Daniel

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik

Inhaltsverzeichnis

Welcome About the author Acknowledgements 1. Readme. before you get started 2. Why learn a programming language as a non-programmer? 3. Setting up R and RStudio 4. The RStudio Interface 5. R Basics: The very fundamentals 6. Starting your R projects 7. Data Wrangling 8. Descriptive Statistics 9. Sources of Bias: Outliers, Normality and other 'Conundrums' 10. Correlations 11. Power: You either have it or you don't 12. Comparing Groups 13. Regression: Creating Models to Predict Future Observations 14. Mixed-Methods Research: Analysing Qualitative Data in R 15. Where to go from here: The next steps in your R journey Epilogue Appendix References

Über Autor(innen)

As a Reader/Associate Professor at the University of Warwick, the author's teaching and research span Organisational Behaviour and Change, International Management, and the development of diagnostic tools for improving organisational outcomes. His research has led to impactful initiatives, such as the Global Education Profiler (GEP), used by universities worldwide to foster social integration on campus and benchmark their internationalisation efforts. These experiences have shaped his ability to create accessible resources, like this book, empowering readers to bridge knowledge gaps and apply analytical techniques confidently to applied settings. His work reflects a commitment to enhancing learning and fostering meaningful change through evidence-based methods by making research tools, like R and RStudio, more accessible.