Course structure
Lectures are structured around theoretical concepts and exercises, coverning different statistical tools and methodologies normally used in forest sciences. Each of these topics is often developed throughout several sequential teaching hours, depending on the time table of each year and the course needs. The topics are not presented in chronological order, as this is adapted to each course timetable and number of students. The assignments are intended to help developing and exercising the theory, related to R and GIS tools.
The lectures are organised in modules (topics), and exercises for a total of 3.5 ECTS. In Finland, 1 ECTS equals 27h of course workload; this course is designed to fulfill 94.5h, distributed in: ca. 28h of direct interaction and lectures, ca. 14h in exercises and the rest in preparing the lectures, assignments and tasks. See the calendar and assignments for further information.
Topic 1. Background concepts
statistical thinking – probability – randomness – distributions
Topic 2. Main tools
expectation – hypothesis tests – p-values – Inference
Topic 3. Models
regression – linear models – parameter estimation – model assessment
Topic 4. Advanced methods
Non-linear models – geostatistics – hierarchical models
Practical methods: R-Materials
R environment – importing data – analysis and models – presentation of results
Practical methods: GIS-Materials
GIS environment – maps – geostatistics – presentation of results
Requirements and evaluation
Grading is from 0 to 5, with 1 being the minimum to pass the course, as standard in the UEF courses. 70% of the grade will be based on the final exam, and 30% of the grade will ne based on the assignments. The assignments are dseign to support learning for the final exam. Notice that not-justified delays in the submission of assignments result in the lowest grade in the overall assessment.
Teaching Methods
- Development of skills by cases and assignments
- In-person teaching methods
- Pre-readings and open discussion of the topics