Information Package / Course Catalogue
IE 435 Risk Analysis
MEF University
Degree Programs
Psychology
General Information For Students
Diploma SupplementErasmus Policy Statement
Psychology
Bachelor Length of the Programme: 4 Number of Credits: 240 TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF: Level 6

Ders Genel Tanıtım Bilgileri

School/Faculty/Institute Faculty of Engineering
Course Code IE 435
Course Title in English Risk Analysis
Course Title in Turkish Risk Analizi
Language of Instruction EN
Type of Course Flipped Classroom,Lecture
Level of Course Advanced
Semester Spring
Contact Hours per Week
Lecture: 3 Recitation: 1 Lab: Other:
Estimated Student Workload 135 hours per semester
Number of Credits 6 ECTS
Grading Mode Standard Letter Grade
Pre-requisites MATH 228 - Probability and Statistics for Engineering II
Expected Prior Knowledge Prior knowledge of basic concepts of probability and statistics is expected
Co-requisites None
Registration Restrictions Only undergraduate students
Overall Educational Objective To acquire knowledge of quantitative analysis concepts with applications using modern tools
Course Description The aim of this course is to introduce important risk concepts and then to teach quantitative risk analysis and control techniques by engineering, economic, environmental and security aspects and to emphasize their role in decision support systems.
Course Description in Turkish Bu dersin amacı önemli risk kavramlarını tanıtmak ve sonrasında mühendislik, ekonomik, çevresel ve güvenlik açılarından niceliksel risk analizi ve kontrol tekniklerini, bunların karar destek sistemlerindeki önemini vurgulamak için öğretmektir.

Course Learning Outcomes and Competences

Upon successful completion of the course, the learner is expected to be able to:
1) Understand important risk concepts to make appropriate analysis;
2) Make risk analysis and optimization with appropriate numerical methods;
3) Use risk as a decision support tool with different dimensions (security, environment, finance, etc.).
Program Learning Outcomes/Course Learning Outcomes 1 2 3
1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology.
2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation.
3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes.
4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts.
5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline.
6) Internalization and dissemination of professional ethical standards.
7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences.
8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level).
9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity.
10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement.
11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses.
12) Ability to acquire knowledge independently, and to plan one’s own learning.
13) Demonstration of advanced competence in the clarity and composition of written work and presentations.

Relation to Program Outcomes and Competences

N None S Supportive H Highly Related
     
Program Outcomes and Competences Level Assessed by
1) Thorough knowledge of the major concepts, theoretical perspectives, empirical findings, and historical trends in psychology. N
2) Understanding of and ability to apply essential research methods in psychology, including research design, data analysis, and data interpretation. N
3) Competence to use critical and creative thinking, skeptical inquiry and a scientific approach to solving problems related to behavior and mental processes. H Exam,HW,Participation
4) Understanding and ability to apply psychological principles, skills and values in personal, social, and organizational contexts. N
5) Ability to weigh evidence, to tolerate ambiguity, and to reflect other values that underpin psychology as a discipline. N
6) Internalization and dissemination of professional ethical standards. N
7) Demonstration of competence in information technologies, and the ability to use computer and other technologies for purposes related to the pursuit of knowledge in psychology and the broader social sciences. N
8) Skills to communicate the knowledge of psychological science effectively, in a variety of formats, in both Turkish and in English (in English, at least CEFR B2 level). N
9) Recognition, understanding, and respect for the complexity of sociocultural and international diversity. S Participation
10) Recognition for the need for, and the skills to pursue, lifelong learning, inquiry, and self-improvement. S HW,Participation
11) Ability to formulate critical hypotheses based on psychological theory and literature, and design studies to test those hypotheses. N
12) Ability to acquire knowledge independently, and to plan one’s own learning. S Exam,HW
13) Demonstration of advanced competence in the clarity and composition of written work and presentations. H Exam,HW
Prepared by and Date ŞİRİN ÖZLEM , December 2023
Course Coordinator TUBA AYHAN
Semester Spring
Name of Instructor Asst. Prof. Dr. ŞİRİN ÖZLEM

Course Contents

Week Subject
1) Historical notes and basic concepts, Semi quantitative risk assessment models
2) Review of probabilistic models
3) Review of statistical models
4) Weibull Analysis
5) Decision Making under Uncertainty
6) Decision Making under Risk
7) Uncertainty modeling and Risk Measurement (DT)
8) Uncertainty modeling and Risk Measurement (BN)
9) Midterm Exam
10) Uncertainty modeling and Risk Measurement (FT)
11) Monte Carlo Simulation
12) Linear and Logistic Regression
13) Project Presentations
14) Project Presentations
Required/Recommended ReadingsRequired: Lecture Notes Recommended: Probabilistic Risk Analysis-Foundations and Methods – Tim Bedford, Roger Cooke
Teaching MethodsFlipped classroom/Exercise/Active learning
Homework and ProjectsTerm Project
Laboratory Work
Computer UseStudents are expected to use computer programs for the course project.
Other Activities
Assessment Methods
Assessment Tools Count Weight
Project 1 % 20
Midterm(s) 2 % 80
TOTAL % 100
Course Administration sirin.ozlem@mef.edu.tr

Attendance/participation: According to YÖK regulations, students are required to attend at least 70% of the lectures. Students are expected to prepare for the lecture via pre-lecture videos and reading materials and attend the lectures. Formal use of e-mails: The course instructor assumes that any information sent through email will be received in 24 hours, unless a system problem occurs. Project: A term project will be assigned to be done in teams of four. Missing the midterm exam: Students missing the midterm exam should get a valid official document to prove their excuse. Missing a final: Faculty regulations. Inappropriate conduct, academic dishonesty and plagiarism are subject to YÖK Disciplinary Regulation.

ECTS Student Workload Estimation

Activity No/Weeks Hours Calculation
No/Weeks per Semester Preparing for the Activity Spent in the Activity Itself Completing the Activity Requirements
Course Hours 14 1.5 3 1.5 84
Project 1 20 9 29
Midterm(s) 1 15 2 17
Final Examination 1 10 2 12
Total Workload 142
Total Workload/25 5.7
ECTS 6