Practical Applications of Biomathematics

Daten

Offizielle Daten in der Fachveröffentlichung für das folgende akademische Jahr: 2023-2024

Thematik

The medical, pharmaceutical, and biotechnological sciences and research methodologies increasingly rely on the use and management of databases and the tools of descriptive and inferential statistics. The course provides overviews of the basics and applications of database management and statistical software packages and support. The Students can get experience and practical skills by solving software-based exercises and problem solving (e.g., Microsoft Excel, RStudio, GPower, Microcal Origin, Minitab). Special emphasis is laid on the application of modern teaching methods (flipped learning, thematic student presentations, and projects, discussion of the Students’ research results, and case studies) in order to provide students with the knowledge, understanding, and hands-on experience in database management and in the mathematical and software toolkit of statistical analysis. The course offers the opportunity to acquire basic mathematical, computer science, and statistical skills that can be helpful in other natural sciences and in preparing diploma work, thesis, or other scientific presentations.

Vorlesungen

• 1. Introduction, data, data management and statistics. - Dr. Bugyi Beáta
• 2. Introduction to software tools. - Dr. Bugyi Beáta
• 3. Principles and applications of descriptive statistics. - Zalai Zsófia
• 4. Principles and applications of descriptive statistics. - Zalai Zsófia
• 5. Principles and applications of inductive statistics. - Dr. Bugyi Beáta
• 6. Principles and applications of inductive statistics. - Dr. Bugyi Beáta
• 7. Correlation and regression analysis. - Leipoldné Dr. Vig Andrea Teréz
• 8. Correlation and regression analysis. - Leipoldné Dr. Vig Andrea Teréz
• 9. Workshop. Discussion of case studies and Students' research results. - Dr. Bugyi Beáta
• 10. Workshop. Discussion of case studies and Students' research results. - Dr. Bugyi Beáta
• 11. Workshop. Students' projects and presentations. - Dr. Bugyi Beáta
• 12. Workshop. Students' projects and presentations. - Dr. Bugyi Beáta

Praktika

Seminare

• 1. Introduction, data, data management and statistics.
• 2. Introduction to software tools.
• 3. Principles and applications of descriptive statistics.
• 4. Data, data management.
• 5. Data, databases.
• 6. Principles and applications of inferential statistics.
• 7. Correlation-, and regression analysis.
• 8. Models, estimation and predictions.
• 9. Discussion of case studies and Students’ research results 1. Workshop.
• 10. Discussion of case studies and Students’ research results 2. Workshop.
• 11. Students’ presentation and projects.
• 12. Revision. Project presentation.

Materialien zum Aneignen des Lehrstoffes

Obligatorische Literatur

Vom Institut veröffentlichter Lehrstoff

Homepage of the Department of Biophysics: https://aok.pte.hu/en/egyseg/10/oktatasi-anyagok

Skript

Empfohlene Literatur

Statistics Openstax, ISBN-10: 1-947172-05-0, ISBN-13: 978-1-947172-05-0
Allan G. Bluman: Elementary statistics, ISBN 978–0–07–338610–2
Myra L- Samuels, Jeffrey A. Witmer, Andrew A. Schaffner: Statistics for the life sciences, ISBN-13: 978-1-292-10181-1
James Stewart, Troy Day: Biocalculus, ISBN-13: 978-1-133-10963-1
J. Pezzullo: Biostatistics for dummies, 2013, Wiley, ISBN 978-1-118-55399-2

Voraussetzung zum Absolvieren des Semesters

Maximum of 25 % absence allowed

Semesteranforderungen

Grading policy
The grade is based on the average result of the following evaluation methods:
result of a written test (expected date: week 12th),
result of Students’ presentations and case studies.
The grade can be improved based on the rules of the Code of Studies and Examinations.

Möglichkeiten zur Nachholung der Fehlzeiten

The opportunity to make up for absence can be discussed with the course leader.

Prüfungsfragen

No exam is scheduled in the exam period.

Prüfer

Praktika, Seminarleiter/innen

• Dr. Bugyi Beáta
• Leipoldné Dr. Vig Andrea Teréz
• Zalai Zsófia