| Course ID: | BBI-SE>DATAANA |
| Course title: | DATA ANALYSIS |
| Semester: | Winter |
| ECTS: | 2 |
| Lectures/Classes: | 0 / 0 hours |
| Field of study: | Bioinformatics |
| Study cycle: | 1st cycle |
| Type of course: | optional |
| Prerequisites: | |
| Contact person: | prof. dr hab. Joanna Szyda joanna.szyda@upwr.edu.pl |
| Short description: | Bioinformatic analysis of biological data covering all analytical stages - from editing the data up to statistical and biological inferences and the presentation of results. Each course uses a different real data set. In case of an above-standard (more hours than officially assigned for the course) involvement in the analysis, it is possible to prepare a publication. |
| Full description: | data analysis, genetics, statistical packages, statistical inference |
| Bibliography: | CRAWLEY M. J. (2007). The R Book. Wiley. SAS online manual http://support.sas.com/documentation/onlinedoc/91pdf/index.html Publikacje w czasopismach naukowych: Genetics, BMC Biology, BMC Bioinformatics, BMC Genetics |
| Learning outcomes: | Knowledge: Knows how to interpret results of biological analyses BI_W04, Has knowledge of the fundamental problems inherent in bioinformatics BI_W10, Knows basic methods of statistical analysis used in the description of biological problems BI_W14 Skills: Applies basic techniques of computer science: can work in various operating systems, knows how to use various software applications, can create simple computer programs and design biological databases BI_U01, Applies basic techniques and research tools in the field of mathematical statistics: knows how to formulate a correct hypothesis, knows how to select the appropriate statistical test, knows how to interpret test results, knows how to model biological data BI_U03, Understands the literature on bioinformatics in English BI_U04 Social competences: Is able to work in a group assuming various roles BI_K03 |
| Assessment methods and assessment criteria: | One mark is given for the course, which includes lectures and labs depending on the number of students enrolled the grade is based on: class attendance, activity during the classes and the individually assigned data analysis project. |