{"product_id":"regression-models-methods-and-applications-applied-regression","title":"Regression: Models, Methods and Applications - Applied Regression","description":"\u003cp\u003eIn this review of Regression: Models, Methods and Applications the bottom line is simple: this is an applied, intermediate-level textbook for readers who need a unified, practical treatment of parametric, nonparametric and semiparametric regression. The reviewer found the book most valuable for students and practitioners who want methods explained on a solid formal basis while staying close to real data work. The emphasis on accessible software and worked case studies makes this a useful bridge between theory and hands-on analysis for applied researchers.\u003c\/p\u003e\n\u003ch2\u003eKey Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eUnified coverage:\u003c\/strong\u003e Presents parametric, nonparametric and semiparametric regression methods in a single volume so readers can compare approaches and choose appropriate models.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eApplied orientation:\u003c\/strong\u003e Emphasizes real data examples and case studies that demonstrate how methods are implemented and interpreted on practical problems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTheoretical foundation:\u003c\/strong\u003e Develops the most important models and methods on a formal basis so students understand assumptions and limitations behind the techniques.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSoftware-aware selection:\u003c\/strong\u003e Prioritizes methods for which user-friendly software is available, helping readers move from theory to reproducible analysis quickly.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTargeted audience guidance:\u003c\/strong\u003e Written at an intermediate mathematical level to suit students and teachers in statistics and applied sciences who require rigor without excessive abstraction.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eWho It's For\u003c\/h2\u003e\n\u003cp\u003eThis book is best for graduate students, instructors and applied researchers in social, economic and life sciences who need a rigorous yet practical treatment of regression methods and prefer examples tied to software. It is also valuable for statistics students and mathematically inclined computer scientists aiming to apply regression methods in data analysis.\u003c\/p\u003e\n\u003cp\u003eReaders who want a beginner's introduction with minimal mathematics, or a purely theoretical monograph focused on proofs at the highest level of abstraction, should look elsewhere. The book assumes some mathematical maturity and a desire to work with real datasets and software.\u003c\/p\u003e\n\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eComprehensive treatment of multiple regression paradigms in one place, making method comparison straightforward.\u003c\/li\u003e\n\u003cli\u003ePractical case studies that show how to apply methods using available software, shortening the path to reproducible analysis.\u003c\/li\u003e\n\u003cli\u003eClear linkage between formal statistical assumptions and applied interpretation, useful for teaching and applied work.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eWritten at an intermediate mathematical level, so it may be challenging for readers seeking an elementary introduction.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eSpecifications\u003c\/h2\u003e\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003eRegression: Models, Methods and Applications\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAuthors\u003c\/td\u003e\n\u003ctd\u003eEndre SuliBosko S. Jovanovic\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eScope\u003c\/td\u003e\n\u003ctd\u003eParametric, nonparametric and semiparametric regression\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eApproach\u003c\/td\u003e\n\u003ctd\u003eApplied with real data examples and case studies\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eLevel\u003c\/td\u003e\n\u003ctd\u003eIntermediate mathematical level\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAudience\u003c\/td\u003e\n\u003ctd\u003eStudents, teachers, and practitioners in applied sciences and statistics\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\n\u003ch2\u003eOur Verdict\u003c\/h2\u003e\n\u003cp\u003eRegression: Models, Methods and Applications is a well-balanced, applied textbook that bridges theory and practice for readers with some mathematical background. Its focus on real data examples and methods supported by user-friendly software makes it good value for graduate students and practitioners who need a rigorous, usable reference for regression modeling.\u003c\/p\u003e\n\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003eDoes the book include software examples?\u003c\/strong\u003e\u003cbr\u003eThe review notes that availability of user-friendly software was a major criterion, and the text emphasizes methods with practical software support.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat level of math is required?\u003c\/strong\u003e\u003cbr\u003eThe book is written at an intermediate mathematical level and assumes some familiarity with statistical concepts and mathematical reasoning.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eIs it suitable for applied researchers?\u003c\/strong\u003e\u003cbr\u003eYes, the applied orientation and case studies make it particularly useful for applied researchers in social, economic and life sciences.\u003c\/p\u003e","brand":"Endre SuliBosko S. 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