ECTS - Engineering Decision and Risk Analysis

Engineering Decision and Risk Analysis (MDES631) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Engineering Decision and Risk Analysis MDES631 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Ph.D.
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives To provide the student with an understanding of the basic concepts of risk analysis and the relationship between probability theory and modeling, risk and decision analysis.
Course Learning Outcomes The students who succeeded in this course;
  • Students can apply probability theory to engineering problems. Students can apply risk analysis to engineering problems.
Course Content Basic notions of probability, random variables, functions of random variables distributions, moments; first and second-order approximations; probability models for engineering analysis; Bernoulli sequence, binomial distribution, Poisson and related distributions, normal and related distributions, extreme-value distributions, other distributions us

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Probability and Statistics in Engineering 1-25
2 Fundamentals of Probability Models 27-39
3 Probability Models 96-131
4 Probability Models 132-150
5 Functions of Random Variables 151-190
6 Statistical Interference 245-259
7 Statistical Interference 262-269
8 Determination of Probability Distribution Models 278-288
9 Determination of Probability Distribution Models 289-301
10 Regression and Correlation 306-313
11 Regression and Correlation 318-339
12 Bayesian Analysis 346-357
13 Bayesian Analysis 360-368
14 Bayesian Analysis 372-381
15 Overall review -
16 Final exam -

Sources

Course Book 1. Ang, A. H. S. and Tang, W. H., Probability Concepts in Engineering, Joh Wiley
Other Sources 2. Ders Notları

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 5 50
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 20
Final Exam/Final Jury 1 30
Toplam 7 100
Percentage of Semester Work 70
Percentage of Final Work 30
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 To become familiar with the state-of-the art and the literature in the software engineering research domain
2 An ability to conduct world-class research in software engineering and publish scholarly articles in top conferences and journals in the area
3 Be able to conduct quantitative and qualitative studies in software engineering
4 Acquire skills needed to bridge software engineering academia and industry and to develop and apply scientific software engineering approaches to solve real-world problems
5 An ability to access information in order to follow recent developments in science and technology and to perform scientific research or implement a project in the software engineering domain.
6 An understanding of professional, legal, ethical and social issues and responsibilities related to Software Engineering.
7 Skills in project and risk management, awareness about importance of entrepreneurship, innovation and long-term development, and recognition of international standards of excellence for software engineering practices standards and methodologies.
8 An understanding about the impact of Software Engineering solutions in a global, environmental, societal and legal context while making decisions.
9 Promote the development, adoption and sustained use of standards of excellence for software engineering practices.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 2 32
Presentation/Seminar Prepration
Project
Report
Homework Assignments 5 6 30
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 15 15
Total Workload 135