| Course title | Practical bio-statistic |
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| Course code | KE/1PBS |
| Organizational form of instruction | Seminary |
| Level of course | unspecified |
| Year of study | not specified |
| Semester | Winter and summer |
| Number of ECTS credits | 5 |
| Language of instruction | English |
| Status of course | unspecified |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Course availability | The course is available to visiting students |
| Lecturer(s) |
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| Course content |
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Statistical analysis can be provided by more or less specialized SW. The free product "R" is used in this course. Students first learn how to manage the data. Then the basic descriptive characteristics are performed and the classical analytical statistical tools employed to test and to model dependencies among variables. The course is taught in English. Preliminary theoretical knowledge of statistics is not required. The course ends with the practical analysis of bio-statistical data. Abstract in detail: 1.FW R-project. Downloading, basic principles, menus, help. 2.R-project. Inserting, re-calculating and saving the data. 3.Types of variables. Categorical variable - frequencies. 4.Continuous variable - quantile and moment characteristics. 5.Computer testing with the use of p-values. 6.Categorical variables - bivariate contingency tables, chi2-test of independency. 7.Continuous variables - t-tests. 8.Analysis of variance (ANOVA) - models and tests. 9.Regression models (1) - simple regression and correlation. 10.Regression models (2) - multiple regression. 11.Time series - description, models and forecasting. 12.Cluster analysis (distance measures, k-means clustering). 13.Survival analysis (survival function, tests, Cox regression).
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| Learning activities and teaching methods |
| unspecified |
| Learning outcomes |
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Analysis of bio-statistical data using specialised SW.
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| Prerequisites |
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unspecified
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| Assessment methods and criteria |
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unspecified
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| Recommended literature |
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| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester |
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