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This core course is designed to provide life science researchers with a foundational understanding of biostatistics, a crucial skill in molecular biology research. While no mathematical background is needed, by the end of the course, you will be comfortable handling and interpreting quantitative data efficiently and effectively.
1. Descriptive Statistics Introduction to Quantitative Data in Molecular Biology - Reporting and Visualizing Quantitative Data
2. Statistical Inference - Understanding Population Space - Error Bars
3. Statistical Testing - Understanding Test Theory - P-Values: Generation and Interpretation - Overview of Common Statistical Tests - Multiple Testing - Power Estimation - ANOVA
4. Experimental Design - Enhancing Experimental Layouts for Reliable Statistics - Distinguishing Between Random and Systematic Errors
5. Supplementary Topics - Introduction to Statistics Software - Time Series Analysis - Correlation Analyses: High-level Overview - Open Science
Throughout the course, students will be guided through showcase examples highlighting critical elements such as qPCR, quantitative imaging, and treatment-response cases. These examples aim to vividly illustrate the application of statistical concepts in real molecular biology scenarios.