Information Package / Course Catalogue
Advanced Data Analysis
Course Code: SPYB550
Course Type: Area Elective
Couse Group: Third Cycle (Doctorate Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

In this course, statistical methods will be introduced using SPSS programme. This course will provide students with statistical concepts, data collection and visualisation techniques, probability and distribution models, hypothesis testing, one-way and two-way analysis of variance, MANOVA, advanced regression analysis, scale development process.

Course Content

Introduction to SPSS, SPSS Menus, Data Entry with SPSS, Calculation of Descriptive Statistics with SPSS, using SPSS programme: Binomial and Poisson Probability Distributions, Confidence Interval, Hypothesis Testing, Regression and Correlation Analyses.

Name of Lecturer(s)
Res. Assist. Ünsal ALTINIŞIK
Learning Outcomes
1.Understand statistical data analysis methods and develop application skills
2.Interpret statistical data correctly and develop the ability to analyse
3.Analyse the decision-making process based on statistical data and develop evaluation skills
4.Develop decision-making skills by using advanced statistical analysis methods
5.To be able to follow current research on advanced statistical data analysis and develop the ability to evaluate it critically
Recommended or Required Reading
1.Montgomery, D. C., Peck, E. A., & Vining, G. G. (2012). Introduction to Linear Regression Analysis (5th ed.).
2.Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J. (2019). Statistics for Business and Economics (14th ed.).
3.DeGroot, M. H., & Schervish, M. J. (2011). Probability and Statistics (4th ed.).
4.McClave, J. T., Benson, P. G., & Sincich, T. (2019). Statistics for Business and Economics (13th ed.).
5.Albright, S. C., Winston, W. L., & Zappe, C. J. (2016). Data Analysis and Decision Making (5th ed.).
Weekly Detailed Course Contents
Week 1 - Theoretical
One-way analysis of variance
Week 2 - Theoretical
Two-way analysis of variance
Week 3 - Theoretical
Repeated measures analysis of variance
Week 4 - Theoretical
MANOVA
Week 5 - Theoretical
Univariate and multivariate linear regression analysis
Week 6 - Theoretical
Logistic regression analysis
Week 7 - Theoretical & Practice
Survival analysis: Life tables, Kaplan-Meier, Logrank test, Cox regression analysis
Week 8 - Theoretical & Practice
ROC analysis
Week 9 - Theoretical & Practice
Use of the "Analysis Selection Diagram" we have developed for the test selection method
Week 10 - Theoretical & Practice
Tabulation with Excel formulas developed for reporting techniques
Week 11 - Theoretical & Practice
Data visualisation
Week 12 - Theoretical & Practice
EndNote usage
Week 13 - Theoretical & Practice
Factor Analysis (Scale Development or Adaptation)
Week 14 - Theoretical & Practice
Factor Analysis (Scale Development or Adaptation) and Review
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory145184
Project1819
Midterm Examination110111
Final Examination116117
TOTAL WORKLOAD (hours)121
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
OÇ-1
1
2
1
1
OÇ-2
1
1
1
OÇ-3
2
1
1
1
OÇ-4
1
1
1
OÇ-5
1
1
1
Adnan Menderes University - Information Package / Course Catalogue
2026