Data Analysis 1

Daten

Offizielle Daten in der Fachveröffentlichung für das folgende akademische Jahr: 2024-2025

Lehrbeauftragte/r

Semesterwochenstunden

Vorlesungen: 6

Praktika: 6

Seminare: 0

Insgesamt: 12

Fachangaben

  • Kode des Kurses: OAF-FMA-T
  • 1 kredit
  • General Medicine
  • Optional modul
  • both
Voraussetzungen:

keine

Zahl der Kursteilnehmer für den Kurs:

min. 5 – max. 12

Thematik

The goal of this course is to help students to prepare for thesis writing or making their own student research project. It covers mainly two fields of that: read and interpret scientific papers and prepare an own study plan. Shortly to say: How to prepare for your own study project.

Block One: The medical papers are likely the most important source to improve your present knowledge as a student and as an MD. Most of these original papers are based on carefully planned data collection and evaluation applying a wide array of statistical methods. It is essential to be familiar with this methodology so to understand these papers. But you may learn these steps and methods from the papers since all are based on the rules of designing scientific research projects. From a paper you may extract the principles as well as you can follow immediately the realization. It is an excellent way to learn the methodology. You may even learn from the errors.

Block Two: Apply all these for your own research: make a study plan. It should include your study goal the extent and way of your data collection the preliminary data processing the way of data analysis and the way of conclusion making.

Based on this outline you will prepare your own study design on your own student’s research work or on your thesis job. If you have no such project at the moment you may construct an own sample study plan that can be a working model for your future thesis work. You will have all help to find your own project and complete the plan in the practice if you need. All of your personal design elements will be discussed and improved by a class discussion.

The practical realization of your study will be supported by the Data analysis 2 course.

Vorlesungen

  • 1. Introduction. Find a paper to process. Find your own study. - Pótó László
  • 2. The goal of your study - based on a demo paper - Pótó László
  • 3. The main- and 'sub-'hypotheses of the study. - Pótó László
  • 4. Finding your sample frame - based on your hypotheses. - Pótó László
  • 5. The research design and the methods of the data collection. How many data should be collected? - Pótó László
  • 6. Creating the plan of the data analysis. The complete study plan. - Pótó László

Praktika

  • 1. Introduction. Overview of some sample papers. - Pótó László
  • 2. The goal of your study - processing a few papers brought and presented by students. - Pótó László
  • 3. Setting the study hypotheses. Further analysis of the papers. - Pótó László
  • 4. Which data should you collect and how to do that. - Pótó László
  • 5. Finalize the plan of your data collection. Make a plan of the data processing. - Pótó László
  • 6. Create, present and discuss of your study plan. - Pótó László

Seminare

Materialien zum Aneignen des Lehrstoffes

Obligatorische Literatur

1-3 medical papers brought by each student (from library, from your department or from the tutor of your thesis).

Vom Institut veröffentlichter Lehrstoff

Other supporting materials supplied by the tutor of the classes.

Skript

Empfohlene Literatur

Any statistical books on study design and data analysis.

Voraussetzung zum Absolvieren des Semesters

Maximum 1 lesson absence.

Semesteranforderungen

Prepare and submit your own study plan step-by-step and present sortly weekly to the group - based on your active participation.

Möglichkeiten zur Nachholung der Fehlzeiten

One extra class

Prüfungsfragen

Preparation of the study plan

Prüfer

Praktika, Seminarleiter/innen

  • Pótó László