Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
4EDS202Statistical Analysis2+2+03406.08.2025

 
Course Details
Language of Instruction Turkish
Level of Course Unit Bachelor's Degree
Department / Program Industrial Engineering
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course It is aimed to provide a more detailed and engineering statistics-focused education on the information obtained in the Probability and Statistics course.
Course Content Detailed content is available in the flow of the course.
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Asist Prof. Ozan Ateş tr.linkedin.com/in/atesozan ozan.ates@outlook.com.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Inferential Statistics, Necmi Gürsakal All Inferential Statistics books
Sampling Methods and Hypothesis Testing, Neyran Orhunbilge
Course Notes WALPOLE R.E., MYERS R.H., MYERS S.L. YE K.E., Probability and Statistics for Engineers and Scientists, 9th Edition, Prentice Hall, 2011.
Documents Örnekleme Yöntemleri ve Hipotez Testleri, Neyran Orhunbilge

Course Category
Mathematics and Basic Sciences %50
Engineering %20
Engineering Design %10
Field %20

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 40
Project 1 % 0
Final examination 1 % 60
Total
3
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 2 28
Hours for off-the-c.r.stud 14 2 28
Mid-terms 1 2 2
Practice 14 2 28
Project 1 14 14
Final examination 1 2 2
Total Work Load   Number of ECTS Credits 4 102

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 The student knows how to use statistical techniques to analyze problems.
2 Students can conduct hypothesis testing and use regression and correlation methods in order to conduct research and analysis.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Representativeness of Samples, Types of Sampling, Statistical Measures Course Notes
2 Lorenz and Pareto (ABC Analysis) from Aggregation Criteria Course Notes
3 Indexes and Moments Course Notes
4 Indexes and Moments Course Notes
5 Confidence Intervals for Population Means, Confidence Intervals for Proportions Course Notes
6 Statistical Tolerance Intervals, Tests and Assumptions Course Notes
7 Statistical Testing Methods and Applications Course Notes
8 Tests on Relationship Measures Course Notes
9 Statistical Relationships (Regression and Correlation) Course Notes
10 Correlation Coefficient Significance Test, Regression Coefficient Significance Test Course Notes
11 Standard Error of Estimate in Regression, Curvilinear Regression Models Course Notes
12 Multiple Regression Models Course Notes
13 Partial Correlation Coefficients Course Notes
14 Rank Correlation, Scales, and Appropriate Statistical Measures Course Notes

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11
All 5 5
C1 5
C2 5

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