'This textbook fills a critical void in the market for statistical tutorials by bridging the gap between elementary and advanced statistics and providing real-world examples in both Stata and R, allowing students to develop proficiency in the statistical software environments in highest demand. It strikes the perfect balance, neither oversimplifying nor overwhelming with complex mathematics, making it the ideal companion for graduate students seeking a solid foundation in the skills needed to generate social science findings with advanced insights. From correlation analysis to multi-level modeling, this comprehensive and versatile book covers a wide range of regression techniques, equipping learners with a diverse toolkit for trustworthy data analysis and allowing them to transition from the classroom to the laboratory with confidence. The authors' expertise shines through in this clear, comprehensive, and engaging book that is destined to be an indispensable resource.' Stephanie Bohon, University of Tennessee
List of figures; List of tables; Preface; 1. Introduction; 2. Undertaking statistical analysis using Stata; 3. Undertaking statistical analysis using R; 4. Descriptive statistics and the normal distribution; 5. Statistical tables and cross-tabulations; 6. Bivariate regression and correlation and statistical inference; 7. Multiple regression and correlation; 8. Regression assumptions and diagnostics and robust regression; 9. Missing data; 10. Issues of survey design; 11. Binomial logistic regression; 12. Ordinal logistic regression; 13. Multinomial logistic regression; 14. Count regression; 15. Survival analysis; 16. Multilevel models; 17. Other issues and final; References; Index.