List of topics

This module offers a comprehensive introduction to biometry, the application of statistical methods to the analysis of biological data. Over the course of 30 hours, students will explore fundamental concepts and techniques used in the collection, analysis, and interpretation of biometric data. Key topics include experimental design, hypothesis testing, regression analysis, and multivariate statistics.

The module combines theoretical lectures with practical sessions, enabling students to apply statistical software to real-world biological datasets. By the end of the course, participants will have acquired the necessary skills to conduct and critically assess biometric analyses in various biological and medical research contexts.

• Overview of Biometry,
• Importance and applications in biological sciences,
• Types of biological data,
• Basic statistical concepts,
• Descriptive statistics,
• Probability distributions,

• Principles of experimental design,
• Randomization and replication,
• Control and treatment groups,

• Null and alternative hypotheses,
• Types of errors (Type I and Type II),
• p-values and significance levels,

• Methods of data collection in biology,
• Data entry and cleaning,
• Introduction to statistical software (e.g., R, Statistica),
• Biometry in medical research,
• Biometry in ecological studies.