ENM5203 Statistical Data Analysis and Decision MakingBahçeşehir UniversityDegree Programs INDUSTRIAL ENGINEERING (ENGLISH, THESIS)General Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
INDUSTRIAL ENGINEERING (ENGLISH, THESIS)
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
ENM5203 Statistical Data Analysis and Decision Making Fall
Spring
3 0 3 12
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Face to face
Course Coordinator : Dr. Öğr. Üyesi ETHEM ÇANAKOĞLU
Course Lecturer(s): Prof. Dr. SELİM ZAİM
Dr. Öğr. Üyesi YÜCEL BATU SALMAN
Recommended Optional Program Components: N/A
Course Objectives: This course provides the use of statistical and quantitative methods using computer technology to examine and explore data. It aims to build and interpret models from this data for decision making in all functional areas.

Learning Outcomes

The students who have succeeded in this course;
Ability to make decisions with statistical methods, ability to collect meaningful data, ability to interpret data and transform it into information/knowledge

Course Content

Methods covered include: collecting data, summarizing and exploring data, hypothesis testing, confidence intervals, regression analysis, ANOVA.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction: Description of data
2) Data collection
3) Descriptive Statistics
4) Confidence intervals
5) Hypothesis testing
6) Hypothesis testing
7) Midterm
8) Regression analysis
9) Regression analysis
10) ANOVA
12) ANOVA
12) SPSS
13) Project presentations
14) Project presentations

Sources

Course Notes / Textbooks: N/A
References: Statistics for Business: Decision Making and Analysis, Robert A. Stine, Dean Foster, Pearson, 2011, 0321123913

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Project 1 % 35
Midterms 1 % 25
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 25
PERCENTAGE OF FINAL WORK % 75
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Study Hours Out of Class 14 4 56
Presentations / Seminar 1 15 15
Project 1 90 90
Midterms 1 40 40
Final 1 60 60
Total Workload 303

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Process view and analytic thinking
2) managerial thinking with technical background
3) To have theoretical knowledge on operations research.
4) Awareness about the applications of operations research
5) To have ability of selection and efficient use of modern techniques, equipments and information technologies for industrial engineering
6) To be capable of designing and conducting experiments and collecting data, analyzing and interpreting results
7) To have verbal and oral effective communication skills by using visual methods in Turkish and English
8) To be aware of entrepreneurship, sustainability and innovation
9) To lead disciplinary and multi-disciplinary teams, to develop solution approaches in complex situations, to work individually and to take responsibility.
10) To have conscious of professional and ethical responsibility
11) To have conscious of necessity to lifelong learning
12) To be aware of economic and legal implications of engineering solutions
13) Economic, social and environmental responsibility while solving management problems