Biological Data Analysis
This course offers practical training in scientific methods and biological data analysis for master students in the biosciences. It covers:
- Scientific hypotheses, study designs, and statistical inference
- The basics of the R language for statistical computing
- Data analysis methods and statistical techniques
- Introduction to the FAIR principles and reproducible science
Knowledge - The student :
- Has advanced knowledge about how to ask proper scientific questions, formulate the corresponding hypotheses, and test these hypotheses based on an appropriate study design
- Has advanced knowledge of how to use relevant data analysis methods, and understand the underlying key statistical principles and general assumptions
Skills - The student :
- can apply visual and statistically analyze simple biological datasets using the software package R
- can use relevant methods to correctly interpret and report statistical results
General competence - The student :
- Can apply good research practices by correctly implementing study designs and statistical principles
- Be familiar with approaches to data management, reproducible science, and the FAIR principles, and develop good practises for storing and sharing data and R code
Compulsory:
Master in B
iosciences and Nordic Master in Sustainable Production and Utilization of Marine Bioresources
Course work:
1) Handing in three exercises addressing R coding and data analysis, delivered before set deadline, and solved in accordance with specifications given for acceptable answers. Evaluation: Approved / not approved. Not approved answers are returned to students for re-delivery. All three exercises must be approved to pass the course.
Exam: Written school exam, 3 hours. 100/100 of total course grade. Grades: A-F
Pen, ruler and up to 2 bilingual dictionaries.
Generating an answer using ChatGPT or similar artificial intelligence and submitting it wholly or partially as one's own answer is considered cheating.