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Emphasizing sound theoretical foundations, this book presents the essential concepts and tools required in finite populations, and systematically develops the Monte Carlo approach in infinite populations to analyze or design complex forest inventories. It thoroughly discusses design-based, model-assisted, and model-dependent inference as well as the design of optimal sampling schemes based on the anticipated variance, the g-weight technique, small area estimation, contingency tables, and transect sampling. The book contains roughly 30 problems with complete solutions as well as case studies and simulations that illustrate the various techniques.