Information Package / Course Catalogue
Health Research and Biostatistics
Course Code: EBE546
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 2
Lab: 0
ECTS: 4
Objectives of the Course

This course aims to teach students how to evaluate data obtained from quantitative and qualitative research conducted in the field of health.

Course Content

Sample determination, data acquisition, data processing, selection of appropriate program and analysis, basic analysis, data evaluation with artificial intelligence, converting analysis into tables and interpretation

Name of Lecturer(s)
Lec. Sibel ŞEKER
Learning Outcomes
1.Ability to calculate sample size for health research
2.Ability to evaluate quantitative and qualitative data in health research and prepare them for analysis.
3.Ability to correctly analyze quantitative and qualitative data obtained in health research with appropriate programs.
4.Ability to analyze data using artificial intelligence
5.Ability to interpret analysis results
Recommended or Required Reading
1.Özdamar, K. (2013). SPSS ile Biyoistatistik. Nisan Kitabevi, Eskişehir.
2.Alpar R. (2014). Spor, Sağlık ve Eğitim Bilimlerinden Örneklerle UYGULAMALI İSTATİSTİK ve GEÇERLİK-GÜVENİRLİK. Detay Yayıncılık, Ankara.
3.Daniel Wayne W. and Chad L. Cross. (2013). Biostatistics: A Foundation for Analysis in the Health Sciences. 10th Edition, New York: John Wiley&Sons.
4.Berthold Lausen, Sabine Krolak-Schwerdt, Matthias Böhmer (2015), Data Science, Learning by Latent Structures, and Knowledge Discovery, Springer-Verlag Berlin
5.Kees van Montfort, Johan Oud, Wendimagegn Ghidey (2014), Developments in Statistical Evaluation of Clinical Trials, Springer Berlin, Heidelberg
6.Thomas J Quirk, Meghan Quirk, Howard F Horton (2015), Excel 2013 for Biological and Life Sciences Statistics, Springer International Publishing Switzerland
7.Ton J. Cleophas, Aeilko H. Zwinderman (2012), SPSS for Starters, Part 2, Springer Dordrecht
8.Hesse-Biber, Sharlene Nagy (2006), The practice of qualitative research, SAGE Publications
Weekly Detailed Course Contents
Week 1 - Theoretical
Determining the number of samples
Week 2 - Theoretical
Data collection methods, data types
Week 3 - Theoretical
Quantitative data analysis programs
Week 4 - Theoretical
Preparing quantitative data for analysis, creating a database
Week 5 - Theoretical
Preparing quantitative data for analysis, creating a database
Week 6 - Theoretical
Evaluating the distribution of quantitative data
Week 7 - Theoretical
Selecting the appropriate analysis to evaluate quantitative data
Week 8 - Theoretical
Sample application to evaluate quantitative data
Week 9 - Theoretical
Qualitative data analysis programs, preparing qualitative data for analysis
Week 10 - Theoretical
Qualitative data analysis
Week 11 - Theoretical
Sample application
Week 12 - Theoretical
Data analysis using artificial intelligence
Week 13 - Theoretical
Sample application
Week 14 - Theoretical
Sample application
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory142256
Midterm Examination112214
Final Examination126228
TOTAL WORKLOAD (hours)98
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
OÇ-1
5
OÇ-2
5
OÇ-3
5
OÇ-4
5
OÇ-5
5
Adnan Menderes University - Information Package / Course Catalogue
2026