The course consists of two separate parts, the probability distributions and their forestry applications, and the second part about sampling schemes in forestry. The course is organized in two parts, to enable students participating either one of the parts, or both of them depending on their primary interests.
The goal of the first part is to provide the students a working knowledge of the statistical theory required for utilizing probability distributions and their properties in forest information systems. It starts with the basic properties of probability distributions and their forest applications. It includes different statistical methods used for estimating the distributions (e.g. maximum likelihood and GLS) and predicting them (e.g. parameter prediction and parameter recovery). Examples of forestry applications are used in exercises.
The goal of the second part is to provide the knowledge required in planning and implementing practical forest inventories, and further developing the existing methods. The second part includes the general theory of sampling based on arbitrary probabilities, use of auxiliary information in design and estimation, and the problems of systematic sampling. In addition, the utilization of the general theory in developing forest applications of the methods is included.
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