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Introduction to the Laws of Statistical Sampling is a clear, concept-driven guide for readers new to statistical sampling, including doctoral students and early-career researchers. Requiring only basic algebra and access to Excel, Bernard Grofman uses simulation and real-world examples--especially from election polling--to build intuition around the Central Limit Theorem and other foundational principles. Structured around six essential questions and ten "laws" of statistical sampling, the book walks readers step by step through reasoning and calculations, highlighting common pitfalls and counterintuitive results. With its accessible language, practical focus, and deep pedagogical insight, this monograph is both a primer for beginners and a valuable refresher for experienced analysts.

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