Forest Biometrics

The book Forest Biometrics is a comprehensive and modern auxiliary textbook intended for first-cycle forestry students. Its aim is to clearly and simply present the fundamental statistical principles used in the forestry profession, connecting theoretical concepts with concrete examples from forestry practice. The authors devote special attention to explaining basic terms, the logic of statistical inference and the practical application of statistical methods in assessing the structure, production and dynamics of forest ecosystems. The textbook is divided into three logically connected parts: General Concepts, Descriptive Statistics and Inferential Statistics. The first section defines statistical populations, variables and elements, providing detailed explanations of mass phenomena (big data), the law of large numbers and the role of sampling in forestry research. The second part discusses descriptive methods — organizing statistical populations, measures of central tendency, variability and distribution shape. Emphasis is placed on practical examples such as classifying breast-height diameters, tree heights and stem volumes. The third part, inferential statistics, introduces the reader to theoretical distributions, parameter estimation, statistical testing and regression analysis. Special emphasis is placed on the application of regression models in determining relationships among structure elements and in constructing forestry tables. The book includes numerous illustrations, tables and real-world examples that help students understand and apply statistical concepts. With its clear writing style, systematic structure and integration of statistics with real forestry problems, Forest Biometrics serves as a valuable tool in educating future forestry engineers and strengthens their ability to conduct scientific research and professional work.