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
Biography
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.
