Data Analysis and Biostatistics
Mastery of the field of pharmacogenomics is not possible without the essential data analysis toolkit. This course covers the general fundamentals of statistics and branches out into methods of defining a sample, testing a hypothesis and comparing one, two or more groups. The course explains methods of comparison that are based on parametric assumptions (e.g., one-way ANOVA) as well as non-parametric tests (e.g., Mann Whitney test). The course also teaches how to design an observational or an experimental study, how to conduct systematic reviews and meta-analysis, and how to model collected data with linear or non-linear regression. As an application of the learned tools, the students will use a statistical software, namely SPSS, to analyze clinical data.
Teaching methods
• Lectures
• Practical sessions
- Course CodeOPPM 104
- ModuleModule 1
- Credit Hours4ECTS/3EG/3LB
- Identify the basic concepts of statistics.
- Choose proper graphical representations according to the type of data.
- Contrast different classifying techniques.
- Visualize and interpret data using software such as SPSS.
- Define study design from different perspectives.
- Apply the biostatistical principles and the different statistical tools in analyzing clinical data.
- Critically evaluate experiments and clinical cases.
- Assess the quality of different studies based on the used statistical methods.
- Integrate statistical knowledge into their broader understanding of the world.
- Make decisions based on their data.
- Discriminate between use and misuse of data analysis.