Information Package / Course Catalogue
Biostatistics and Data Analysis in Child Development
Course Code: ÇGEL512
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 1
Credit: 4
Lab: 0
ECTS: 8
Objectives of the Course

The aim of this course is to enable students to learn basic biostatistical methods used in child development and social sciences, to conduct data collection, analysis, interpretation, and reporting processes in scientific research, and to perform appropriate statistical analyses using SPSS software.

Course Content

This course covers the scientific research process, data types, variables, scale types, data organization and visualization, descriptive statistics, normality analysis, parametric and non-parametric tests, correlation and regression analyses, scale reliability analyses, data entry and statistical applications using SPSS software, interpretation of findings, and academic reporting processes.

Name of Lecturer(s)
Learning Outcomes
1.Explain basic biostatistical concepts used in scientific research.
2.Select appropriate statistical analysis methods for research problems.
3.Perform data entry, organization, and statistical analyses using SPSS.
4.Conduct parametric and non-parametric analyses.
5.Interpret correlation and regression analyses.
6.Evaluate scale reliability analyses.
7.Report statistical findings according to academic writing standards.
Recommended or Required Reading
1.Büyüköztürk, Ş. (2023). Sosyal Bilimler İçin Veri Analizi El Kitabı. Pegem Akademi.
2.Can, A. (2022). SPSS ile Bilimsel Araştırma Sürecinde Nicel Veri Analizi. Pegem Akademi.
Weekly Detailed Course Contents
Week 1 - Theoretical
Scientific research process and basic statistical concepts
Week 2 - Theoretical
Variable types, scales, and data collection methods
Week 3 - Theoretical & Practice
Introduction to SPSS and data entry applications
Week 4 - Theoretical & Practice
Data editing, coding, and data cleaning procedures
Week 5 - Theoretical & Practice
Descriptive statistics and data visualization
Week 6 - Theoretical & Practice
Normality analysis and selection of appropriate tests
Week 7 - Theoretical & Practice
Parametric tests: t-test and ANOVA applications
Week 8 - Theoretical & Practice
Non-parametric tests
Week 9 - Theoretical & Practice
Correlation analyses
Week 10 - Theoretical & Practice
Simple and multiple regression analyses
Week 11 - Theoretical & Practice
Reliability analyses and scale evaluation
Week 12 - Theoretical & Practice
Interpretation of SPSS outputs and table preparation
Week 13 - Theoretical & Practice
Academic reporting and APA-style result writing
Week 14 - Theoretical & Practice
Applied data analysis presentations and overall evaluation
Assessment Methods and Criteria
Type of AssessmentCountPercent
Assignment1%15
Midterm Examination1%25
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory142370
Lecture - Practice142256
Assignment26216
Presentation 1415
Individual Work121348
Midterm Examination1224
Final Examination1325
TOTAL WORKLOAD (hours)204
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
PÇ-10
OÇ-1
3
4
4
3
3
3
1
2
2
2
OÇ-2
2
5
5
4
4
3
1
3
2
3
OÇ-3
2
4
5
5
4
4
1
3
2
2
OÇ-4
2
4
5
5
4
4
1
3
3
3
OÇ-5
2
4
4
4
5
4
2
4
3
4
OÇ-6
2
3
4
4
4
3
1
3
3
5
OÇ-7
2
4
5
4
5
4
2
4
3
4
Adnan Menderes University - Information Package / Course Catalogue
2026