Information Package / Course Catalogue - Adnan Menderes University

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Advanced Statistical Data Analysis

Course Code	: UTFY523
Course Type	: Area Elective
Couse Group	: Second Cycle (Master's Degree)
Education Language	: Turkish
Work Placement	: N/A

Theory	: 3
Prt.	: 0
Credit	: 3
Lab	: 0
ECTS	: 5

Objectives of the Course

The objective of this course is to provide students with advanced statistical analysis techniques, improve their data-driven research skills, and enable the practical application of statistical methods commonly used in scientific studies.

Course Content

This course covers advanced statistical data analysis techniques used in social sciences, economics, finance, and international trade. The course focuses on data preparation, multivariate statistical methods, dimensionality reduction techniques, cluster analysis, regression models, and applied data analysis procedures. Students gain practical experience using real-world datasets and contemporary statistical methods employed in scientific research.

Name of Lecturer(s)

Learning Outcomes

1.	Apply advanced statistical analyses.
2.	Analyze multivariate datasets.
3.	Use dimensionality reduction techniques.
4.	Apply clustering and classification methods.
5.	Interpret research data scientifically.

Recommended or Required Reading

1.	Agresti, A. (2018). Statistical Methods for the Social Sciences.
2.	Everitt, B., & Hothorn, T. (2011). An Introduction to Applied Multivariate Analysis with R.
3.	Field, A. (2024). Discovering Statistics Using IBM SPSS Statistics.
4.	Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2022). Multivariate Data Analysis.
5.	James, G., Witten, D., Hastie, T., & Tibshirani, R. (2023). An Introduction to Statistical Learning.

Weekly Detailed Course Contents

Week 1 - Theoretical

Introduction to Advanced Statistical Analysis

Week 2 - Theoretical

Data Preparation and Preprocessing

Week 3 - Theoretical

Exploratory Data Analysis

Week 4 - Theoretical

Multiple Regression Analysis Hafta 5 / Week 5

Week 5 - Theoretical

Logistic Regression

Week 6 - Theoretical

Statistical Assumption Testing

Week 7 - Theoretical

Factor Analysis

Week 8 - Theoretical

Principal Component Analysis (PCA)

Week 9 - Theoretical

Cluster Analysis

Week 10 - Theoretical

Discriminant Analysis

Week 11 - Theoretical

Confirmatory Factor Analysis

Week 12 - Theoretical

Introduction to Structural Equation Modeling

Week 13 - Theoretical

Applied Research Analyses

Week 14 - Theoretical

Term Project Presentations

Assessment Methods and Criteria

Type of Assessment	Count	Percent
Midterm Examination	1	%40
Final Examination	1	%60

Workload Calculation

Activities	Count	Preparation	Time	Total Work Load (hours)
Lecture - Theory	14	8	0	112
Midterm Examination	1	5	0	5
Final Examination	1	8	0	8
TOTAL WORKLOAD (hours)				125

Contribution of Learning Outcomes to Programme Outcomes

	PÇ-1	PÇ-2	PÇ-3	PÇ-4	PÇ-5
OÇ-1	5	5	5	5	5
OÇ-2	5	5	5	5	5
OÇ-3	5	5	5	4	5
OÇ-4	4	5	5	5	5
OÇ-5	5	5	5	5	5

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