Biostatistics (SL_003)
About Study Course
Objective
To acquire knowledge and skills in the statistical data processing methods used in biomedicine (descriptive statistics, inferential statistics for assessing differences and exploring relationships between different variables), which are necessary for the development of a scientific research thesis at Master's level, for an in-depth analysis of scientific publications and for the correct recording of the results of quantitative research.
Prerequisites
Knowledge in mathematics and informatics corresponding to the level of secondary education. Basic knowledge of statistics and research design is preferred.
Learning outcomes
Upon successful completion of the course, students will have acquired knowledge that allows to:
* recognise terminology used in statistics and basic methods used in different publications;
* know the most often used possibilities offered by MS Excel and IBM SPSS in data processing;
* know the criteria for using data processing methods;
* interpret the most important statistical indicators correctly.
After completion of this course, students will be able to: *enter and edit data in computer programs MS Excel and IBM SPSS;
*prepare data for statistical processing correctly;
*choose appropriate data processing methods, incl., statistical hypothesis testing;
*process research data statistically using computer programs MS Excel and IBM SPSS;
*create tables and charts for the results obtained by MS Excel and IBM SPSS programs;
*describe the obtained research results precisely.
After completion of this course, students will be able to make reasoned decisions about the use of statistical data processing methods to achieve research aims, and using computer programs MS Excel and IBM SPSS, practically apply the learned basic statistical methods in research data processing.
Study course planning
| Study programme | Study semester | Program level | Study course category | Lecturers | Schedule |
|---|---|---|---|---|---|
| Biomedicine, MFMB | 2 | Master’s | Required | Māra Grēve |
