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SECOND CYCLE - MASTER'S DEGREE
THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
INDUSTRIAL ENGINEERING DEPARTMENT
1261 Industrial Engineering
Course Information
Course Learning Outcomes
Course's Contribution To Program
ECTS Workload
Course Details
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COURSE INFORMATION
Course Code
Course Title
L+P Hour
Semester
ECTS
ENM 523
ADVANCED INVENTORY MANAGEMENT
3 + 0
2nd Semester
7,5
COURSE DESCRIPTION
Course Level
Master's Degree
Course Type
Elective
Course Objective
Analyzing and interpreting data is important in decision processes under uncertainty. Therefore, under which circumstances multivariate statistical techniques are used, what the assumptions of these techniques and how to interpret the results of these techniques are scopes of this course. This course will help all students to understand and use these advanced techniques who are in need of analyzing data.
Course Content
Classification of multivariate techniques and statistical fundamentals, Calculation of descriptive statistics, Parametric tests (z and t tests, One-Way and Two-Way ANOVA Analysis), Non-parametric tests (Chi- Square Test, Kruskal-Wallis (K-W) H Test, Kolmogrov-Simirnov Test), Linear Regression Analysis, Logistic Regression Analysis, Reliability and Questions Analysis
Prerequisites
No the prerequisite of lesson.
Corequisite
No the corequisite of lesson.
Mode of Delivery
Face to Face
COURSE LEARNING OUTCOMES
1
Students have information about the basic concepts of statistics
2
Students gain the ability of using statistical methods and relevant tools such as SPSS.
COURSE'S CONTRIBUTION TO PROGRAM
PO 01
PO 02
PO 03
PO 04
PO 05
PO 06
PO 07
PO 08
PO 09
PO 10
LO 001
4
4
4
4
4
2
2
2
2
3
LO 002
5
5
5
5
5
3
3
2
2
5
Sub Total
9
9
9
9
9
5
5
4
4
8
Contribution
5
5
5
5
5
3
3
2
2
4
ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities
Quantity
Duration (Hour)
Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)
14
3
42
Assignments
4
5
20
Mid-terms
1
60
60
Final examination
1
73
73
Total Work Load
ECTS Credit of the Course
195
7,5
COURSE DETAILS
Select Year
All Years
2020-2021 Spring
2018-2019 Fall
2017-2018 Fall
2008-2009 Fall
2007-2008 Fall
Course Term
No
Instructors
Details
2018-2019 Fall
1
HASAN AKYER
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Course Details
Course Code
Course Title
L+P Hour
Course Code
Language Of Instruction
Course Semester
ENM 523
ADVANCED INVENTORY MANAGEMENT
3 + 0
1
Turkish
2018-2019 Fall
Course Coordinator
E-Mail
Phone Number
Course Location
Attendance
Asts. Prof. Dr. HASAN AKYER
hakyer@pau.edu.tr
MUH A0425
%
Goals
Analyzing and interpreting data is important in decision processes under uncertainty. Therefore, under which circumstances multivariate statistical techniques are used, what the assumptions of these techniques and how to interpret the results of these techniques are scopes of this course. This course will help all students to understand and use these advanced techniques who are in need of analyzing data.
Content
Classification of multivariate techniques and statistical fundamentals, Calculation of descriptive statistics, Parametric tests (z and t tests, One-Way and Two-Way ANOVA Analysis), Non-parametric tests (Chi- Square Test, Kruskal-Wallis (K-W) H Test, Kolmogrov-Simirnov Test), Linear Regression Analysis, Logistic Regression Analysis, Reliability and Questions Analysis
Topics
Weeks
Topics
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Materials
Materials are not specified.
Resources
Course Assessment
Assesment Methods
Percentage (%)
Assesment Methods Title
Final Exam
50
Final Exam
Midterm Exam
50
Midterm Exam
L+P:
Lecture and Practice
PQ:
Program Learning Outcomes
LO:
Course Learning Outcomes
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Home Page
About University
Name And Address
Acedemic Authorities
General Discription
Academic Calendar
General Admission Requirements
Recognition of Prior Learning
General Registration Procedures
ECTS Credit Allocation
Academic Guidance
Information For Students
Cost Of Living
Accommodation
Meals
Medical Facilities
Facilities for Special Needs Students
Insurance
Financial Support for Students
Student Affairs
Learning Facilities
International Programs
Language Courses
Internships
Sports Facilities and Leisure Activities
Student Associations
Practical Information for Mobile Students
Degree Programmes