Conducted in
terms:
2022/23Z, 2023/24Z
Erasmus code: 13.1
ISCED code: 0511
ECTS credits:
3
Language:
English
Organized by:
Faculty of Biological and Veterinary Sciences
(for:
Nicolaus Copernicus University in Toruń)
Basic of statistics and multivariate analyses for biologists 2600-OG-EN-BSM
Classes include the application statistical methods in biology: description of biological data, description of relationships by means of basic linear and nonlinear functions, parametric and nonparametric significance tests, linear regression, classification, indirect and direct ordination methods.Students are welcome to work with their own data and solve research questions of any branch of biology.
Total student workload
Contact hours with teacher:
- participation in laboratory and lecture - 30 hrs
- consultations - 10 hrs
Self-study hours:
- preparation for laboratory - 10 hrs
Altogether: 50 hrs (2 ECTS)
Learning outcomes - knowledge
Student
W1: defines a task or problem in the field of biology and selects appropriate statistical methods to solve them K_W11
Learning outcomes - skills
Student
U1: applies basics knowledge in the field of statistics to the biological data and is able to use computer software for calculation and presentation of the results K_U06, K_U07
U2: is able to use a foreign language to communicate at a basic level in accordance with the requirements of B2 ESOKJ K_U17
U3: has the ability to present results in English, as well as write a report in English K_U22, K_U21
Learning outcomes - social competencies
Student
K1: demonstrates the ability to use statistical and multivariate methods to develop and present results and analyzes K_K07
K2: can work in a team, both by directing and co-ordinating the team's activities and by performing assigned tasks K_K11
Teaching methods
Expository teaching methods:
discussion, presentation, video / computer, pointer, banners image
Observation/demonstration teaching methods
- display
Expository teaching methods
- informative (conventional) lecture
- problem-based lecture
- problem-based lecture
Exploratory teaching methods
- project work
- laboratory
- case study
- presentation of a paper
- laboratory
- case study
- presentation of a paper
Type of course
elective course
Prerequisites
Basic knowledge of statistics in the field of first degree studies.
Course coordinators
Assessment criteria
Laboratory – project in groups 61-68% satisfactory, 69-76% satisfactory plus, 77-84 % good, 85- 92% good plus, 93-100% very good W1, W2, U1, U2, K1
Practical placement
not applicable
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: