ECTS
ECTS Course Catalogue
Course details
Course code: BBS20246o17Semester: 2017/2018 winter
Name: Statistical Methods in Biology
Major: Biology
Study Type: second cycle
Course type: compulsory
Study Semester: 1
ECTS points: 5
Hours (Lectures / Tutorials / Other): 15 / 15 / 0
Lecturer: prof. dr hab. Joanna Szyda
Language of instruction: Polish / English
The course taught in English if the group has ≥6 students. The course taught in Polish with a possibility of support in English if the group has <6 students.
Learning outcomes: Knowledge: Student: has the knowledge to interpret biological phenomena and processes in research and practical activities; knows the research methodology applicable in the natural sciences; formulates research hypotheses, and solves basic scientific problems; knows how to create interesting multimedia presentation; describes and explains the biological phenomena in mathematical terms; understands the importance of methods of descriptive statistics and mathematical modeling in description and interpretation of biological phenomena and processes, in the statistical analysis of data and in obtaining and processing information; knows the most important statistical tools to assess the course of natural phenomena and processes; knows the applicability of parametric and nonparametric tests. Skills: Student: applies appropriate statistical methods for data analysis, the description of phenomena and for hypotheses testing; based on data analysis formulates and interprets the results of research tasks. Skillfully juxtaposes them in tables and illustrates them graphically; draws the appropriate conclusions and makes appropriate judgments.
Competences: Student: is willing to regularly update knowledge on biology and related disciplines, and conscious of the need for learning throughout life; is active in improving skills through courses and specialized training and the literature; is able to inspire and organize the learning process of others.
Prerequisites: none
Course content: Populations and samples, hypotheses testing, parameter estimation, experimental design, the most commonly used statistical tests, linear regression, nonlinear regression, determine the quality of the fit equation of linear and nonlinear regression, correlation, elements of statistical modeling, model selection, analysis of variance, analysis of covariance.
Recommended literature: 1. Collett, D. (1991) Modelling Binary Data, Chapmann and Hall 2. Draper, N.R., Smith, H. (1998) Applied Regression Analysis, Wiley 3. Hawkins, D. (2005) Biomeasurement. Understanding, analysing, and communicating data in the biosciences. Oxford University Press 4. Ruxton and Colegrave (2003) Experimental design for the life sciences.
Assessment methods: Assessment of tutorials: Based on points scored by the students during the two tests. It is required to have at least 50% of possible points in order to obtain a positive evaluation. The final grade can be enhanced by student’s active participation in tutorials. The presence at tutorials is compulsory. Completion of the course: students with a valid credit for a tutorial undergo a written or oral exam (5-10 open questions) in the examination session. The written examination lasts up to 90 minut
Comment: Lectures should take place in the hall with Internet access. Computer labs should take place in the room with Internet access and personal computers with the required software. Each student has individual access to a computing terminal.