BIO604 Advanced statistical methods in ecology, evolution and environmental sciences

The course is connected to the following study programs

• PhD Programme in Engineering and Science

Teaching language

English, unless all participants are Norwegian. 

Prerequisites

MSc degree and basic statistical knowledge (for instance BIO403 or relevant work experience). Interested MSc students can apply to be enrolled.  

Recommended prerequisites

Experience with R or another coding language such as C, Julia, or Python. 

Course contents

Quantitative methods used in ecology, evolution, and environmental sciences. The contents of each iteration of the course will be given well in advance of the application deadline. 

Learning outcomes

This course is designed to provide PhD fellows with in-depth knowledge of quantitative research methods. The contents can to some degrees be tailored to the individual candidates’ needs. 

After having completed the course, the students will: 

• have acquired advanced knowledge within specific themes of statistical methodology in ecology, evolution, or environmental sciences 

• have improved their programming skills 

• be able to critically evaluate advantages and limitations of different statistical methods 

• be able to prepare teaching materials for specific topics 

• have implemented routines for reproducible science 

Examination requirements

At least 90 % attendance on compulsory learning activities including student-prepared teaching materials and peer review. Details will be given in Canvas at the start of the course.

Teaching methods

Lectures, seminars, and practical exercises. The students will prepare and present teaching materials for a chosen topic and will peer review each other’s materials. There is a large degree of flexibility regarding course content and methods that can be tailored to the individu More information will be given in Canvas at the start of the course.al candidate’s needs. The course will be given as an on-campus/digital hybrid. The estimated student workload in this course is 135 hours. 

Evaluation

Emneansvarlig fastsetter i samråd med studenttillitsvalgt evalueringsform og om emnene skal ha midtveis- eller sluttevaluering i tråd med kvalitetssystemet kapittel 4.1. Informasjon om evalueringsform for emnet publiseres i Canvas.

Offered as Single Standing Module

Yes

Admission Requirement if given as Single Standing Module

PhD candidates. Applicants with relevant scientific background can be considered if the resources are available. 

Assessment methods and criteria

Individually written report and seminar based on analyses of own data. Graded pass/fail.The report must be approved in order to be able to present it at the seminar. Both partial exams must be passed. More information will be given in Canvas at the start of the course