Upon a successful completion of this course, the students are expected to be able to understand the principles of research methodology in forestry, taking into account the research issue and objective formulation as well as choosing an appropriate research approach, experimental set-up, and sampling technique. The students will be able to understand basic biometric and ecosystem modeling concepts, and to apply basic commands of R statistics to model and analyse the collected data. In addition, the students will be able to critically evaluate accuracy, error types, and reproducibility of research results. Finally, they will understand the basic concepts in Geographic Information Systems and remote sensing techniques, and use the basic GIS software to solve spatial problems, and perceive the potential for forestry-related research.

Applied statistics, research methodology, biometric and ecosystem modeling concepts, R statistics, GIS and remote sensing techniques.

Lectures on research, data analysis, statistical concepts and methods (28 h), practical exercises with R statistics and GIS software (14 h). Modeling group work and learning diary.

Autumn 2020 online. The webpage of the course is at: https://wiki.uef.fi/display/RESMET/Home

Hamilton, L.C. (1992) Regression with Graphics, A second course in applied statistics. Duxbury Press.

Wonnacott, R. & Wonnacott, T., (1985) Introductory Statistics, 4th edition, John Wiley and Sons.

Course notes and selected online materials: https://wiki.uef.fi/display/RESMET/Home

0-5 Assignments (30%) and final examination (70%)

 Senior Researcher Blas Mola and adjunct instructors.

Autumn 2021

Joensuu

The language of instruction for this course is English. It is recommended to take this course together with Academic skills in forest sciences (3513061). The course is intended only for MSc degree students.