SUMMARY
The forum discussion identifies several recommended books on mathematical statistics suitable for math and engineering students. Key titles include "Statistics in Plain English, Third Edition" by Timothy C. Urdan, "Introductory Statistics" by Neil A. Weiss, and "Statistics, 4th Edition" by David Freedman, Robert Pisani, and Roger Purves. For advanced learners, "A First Course in Mathematical Statistics" by C. E. Weatherburn and "Theoretical Statistics" by D. R. Cox are highlighted. Additional resources include the "Mathematical Handbook for Scientists and Engineers" by Granino A. Korn and Theresa M. Korn, and Casella and Berger's "Statistical Inference."
PREREQUISITES
- Basic understanding of statistical concepts
- Familiarity with mathematical notation
- Knowledge of probability theory
- Experience with data analysis techniques
NEXT STEPS
- Explore "Statistics in Plain English, Third Edition" for foundational concepts
- Study "A First Course in Mathematical Statistics" for advanced statistical methods
- Review "Theoretical Statistics" by D. R. Cox for in-depth theoretical insights
- Access the MIT OpenCourseWare for additional mathematical statistics resources
USEFUL FOR
Students in mathematics and engineering disciplines, educators seeking teaching materials, and professionals looking to enhance their statistical analysis skills will benefit from this discussion.