Introduction into basic design and evaluation of biological and medical research experiments

Data

Official data in SubjectManager for the following academic year: 2026-2027

Topic

The aim of the course is to introduce students to the fundamental concepts of data management and statistics used in biological and biomedical research, and to provide practical skills for using modern tools required for data analysis. During the course, students will become familiar with proper data structuring, basic statistical thinking, the principles of hypothesis testing, and the key aspects of experimental design. The training places particular emphasis on the problem of multiple comparisons, the interpretation of statistical power and effect size, as well as the specific challenges associated with the analysis of omics data. Through practical examples, students will learn data management in Excel and RStudio environments, and within the framework of a small project they will develop an analysis plan related to their own research question.

The course aims to develop critical statistical thinking and to support students in independently and soundly interpreting, analyzing, and presenting their research data.

Lectures

• 1. Course introduction, principles of data management, and Excel basics - Takács-Lovász Krisztina
• 2. Data types and basic statistics - Takács-Lovász Krisztina
• 3. Characterization of data distributions - Takács-Lovász Krisztina
• 4. Research questions, hypothesis formulation, and statistical thinking - Takács-Lovász Krisztina
• 5. Multiple comparisons (multiple testing, FDR, Bonferroni, omics examples) - Takács-Lovász Krisztina
• 6. Power analysis and effect size estimation - Takács-Lovász Krisztina
• 7. Clustering - Takács-Lovász Krisztina
• 8. Investigating relationships between variables - Takács-Lovász Krisztina
• 9. Regression analysis - Takács-Lovász Krisztina
• 10.

  Experimental design in a laboratory setting

  - Kecskés Angéla

Practices

• 1. Practical example - Takács-Lovász Krisztina
• 2. Practical example; Brainstorming ideas for one’s own experiment/project - Takács-Lovász Krisztina

Seminars

Reading material

Obligatory literature

Literature developed by the Department

Notes

Recommended literature

Molecular Data Analysis Using R / Csaba Ortutay, Zsuzsanna Ortutay / Hoboken, NJ : John Wiley & Sons, Inc. , [2017]

Shahbaba, Babak. (2012). Biostatistics with R: An Introduction to Statistics Through Biological Data. 10.1007/978-1-4614-1302-8.

Conditions for acceptance of the semester

Laptop for the practical sessions.

Mid-term exams

In the form of answers to short questions that aid understanding of the subject matter.

Making up for missed classes

Written assignment

Exam topics/questions

-

Examiners

Instructor / tutor of practices and seminars

• Takács-Lovász Krisztina