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This volume provides a comprehensive introduction to the principles and practices of experimental design, a cornerstone of empirical research across disciplines. Covering foundational topics such as sampling, randomization, and analysis of variance, alongside more advanced methods like factorial designs and multivariate approaches, this volume equips readers to design rigorous experiments with confidence.
Whether you're preparing for exams, conducting field studies, or planning business trials, this book offers practical guidance through real-world examples ranging from A/B testing in digital marketing to policy evaluations in the public sector.
Designed for students, researchers, and practitioners alike, it emphasizes not only the technical aspects of design and analysis, but also the interpretation of results for decision-making. Readers will gain the skills to produce credible causal evidence and translate findings into actionable insights.
Info autore
Dr. Mike Nguyen is a professor of marketing and data science whose research is deeply informed by active collaborations with firms in telecommunications, financial institutions, and digital platforms. He teaches data analytics and causal inference at both undergraduate and graduate levels, with an emphasis on business applications in marketing, finance, and strategic decision-making. His work integrates econometrics, machine learning, and experimental design to tackle real-world problems. Dr. Nguyen designs research-based solutions in partnership with industry to inform both theory and practice. This book reflects his commitment to accessibility—offering intuitive explanations for practitioners and students—while also providing the mathematical foundations and references required for graduate and PhD-level study.
Riassunto
This volume provides a comprehensive introduction to the principles and practices of experimental design, a cornerstone of empirical research across disciplines. Covering foundational topics such as sampling, randomization, and analysis of variance, alongside more advanced methods like factorial designs and multivariate approaches, this volume equips readers to design rigorous experiments with confidence.
Whether you're preparing for exams, conducting field studies, or planning business trials, this book offers practical guidance through real-world examples—ranging from A/B testing in digital marketing to policy evaluations in the public sector.
Designed for students, researchers, and practitioners alike, it emphasizes not only the technical aspects of design and analysis, but also the interpretation of results for decision-making. Readers will gain the skills to produce credible causal evidence and translate findings into actionable insights.
