This book is based on our original lecture materials. In 1993, Juha wrote a 182-page booklet entitled “Methods for Forest Biometry” that described intermediate and advanced statistics for Finnish foresters. About 15 years later, Lauri took over responsibility for the biometrics course at the Universities of Helsinki and Joensuu, and wrote his own lectures, which covered a smaller number of detailed topics, but where everything was demonstrated using the statistical program R. In 2013, motivated by a suggestion from Timo Tokola, we decided to combine the essential contents of these two material sources for an international audience. Writing a book was much more time consuming than we expected. Now after many years, the book is finally published. The contents of the book are quite diverse. However, we have tried to keep it as selfsufficient as possible. Therefore, the first chapters cover the basics of probability calculus and estimation theory, while in the later chapters there is also some new material. Originally, we had planned to cover many more topics, but we had to drop some of them due to limitations in time and space. For example, the widely used kNN method is only briefly noted in Section 13.2.2 and Chapter 11. We are not including references to those results of basic statistical theory that are well described in publicly available high-quality sites in the Internet. 1. Introduction 2. Random Variables 3. Statistical Modeling, Estimation and Prediction 4. Linear Model 5. Linear Mixed-effects Models 6. More about Linear Mixed-eff□ects Models 7. Nonlinear (Mixed-eff□ects) Models 8. Generalized Linear (Mixed-E□ffects) Models 9. Multivariate (Mixed-Eff□ects) Models 10. Additional topics on regression 11. Modeling Tree Size 12. Taper Curves 13. Measurement Errors 14. Forest and Environmental Experiments
