Information Package / Course Catalogue
Data Analysis – II
Course Code: EKO520
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 main objective of this course is to provide a basic understanding of data analysis concepts and to use it in applicons with the R software. The course will cover basic approaches in statistical inference as well as an introduction to basic machine learning algorithms.

Course Content

The main subjects of the course are graphical and quantitative methods to describe data, using statistics models, verifying model assumptions using statistics, testing hypothesis and applying basic machine learining algorithms in engineering problems.

Name of Lecturer(s)
Learning Outcomes
1.Describe various styles of interpretation of qualitative data
2.Articulate the relative appropriateness of different analysis approaches for a particular qualitative study
3.Have enough knowledge of mathematics to understand the theory and application of statistics
4.To be able to use the resources related to statistics
5.Can use the abstract and analytical thinking ability
Recommended or Required Reading
1.SPSS ile veri analizi, Nuran Bayram, N.(2009), SPSS ile veri analizi, Seçkin yayıncılık, Ankara.
Weekly Detailed Course Contents
Week 1 - Theoretical
Compilation of data
Week 2 - Theoretical
Transferring data to a computer
Week 3 - Theoretical
Tables and Charts
Week 4 - Theoretical
Averages
Week 5 - Theoretical
Dispersion and tilt measurements
Week 6 - Theoretical
Index numbers
Week 7 - Intermediate Exam
Revision of Midterm Exams
Week 8 - Intermediate Exam
Midterm Exams
Week 9 - Theoretical
Regression and correlation analysis
Week 10 - Theoretical
Hypothesis testing
Week 11 - Theoretical
Hypothesis testing
Week 12 - Theoretical
Non-parametric tests
Week 13 - Theoretical
Non-parametric tests
Week 14 - Theoretical
Non-parametric tests
Week 15 - Final Exam
Final Exams
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory153390
Midterm Examination110212
Final Examination120222
TOTAL WORKLOAD (hours)124
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
PÇ-11
PÇ-12
PÇ-13
OÇ-1
4
4
4
4
4
4
4
4
4
4
4
4
4
OÇ-2
4
4
4
4
4
4
4
4
4
4
4
4
4
OÇ-3
4
4
4
4
4
4
4
4
4
4
4
4
4
OÇ-4
4
4
4
4
4
4
4
4
4
4
4
4
4
OÇ-5
4
4
4
4
4
4
4
4
4
4
4
4
4
Adnan Menderes University - Information Package / Course Catalogue