MATH 240 | Course Introduction and Application Information

Course Name
Probability for Engineers
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
MATH 240
Spring
3
0
3
6

Prerequisites
  MATH 154 To get a grade of at least FD
Course Language
English
Course Type
Required
Course Level
First Cycle
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives This course aims to introduce students the theory of probability and its applications to engineering problems.
Course Description The students who succeeded in this course;
  • will be able to use fundamental concepts such as additon rule, conditional probability, and independence
  • will be able to use the total probability rule and Bayes' theorem
  • will be able to use discrete random variables and their distributions
  • will be able to use continuous random variables and their distributions
  • will be able to use joint probability distributions
Course Content Topics of this course include the axioms of probability, Bayes' theorem, random variables and sums of random variables, law of large numbers, the central limit theorem and its applications.

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introduction to Probability Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 2- P64-71)
2 Counting Techniques Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 2- P64-71)
3 Counting Techniques Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 2- P64-71)
4 Counting Techniques Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 2- P64-71)
5 Conditional probabilities Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 2- P82-91)
6 Bayes’ rule Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 2- P92-97)
7 Discrete random variables Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 3 P104-107)
8 Continuous random variables Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 3 P107-113)
9 Mathematical Expectation Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 4 P148-159)
10 Joint Probability distributions Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 3 P114-127)
11 Mathematical Expectation Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 4 P131-147)
12 Some Discrete Probability Distributions Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 5 P163-186)
13 Some Continuous Probability Distributions Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 6 P191-214)
14 Some Continuous Probability Distributions Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill. (Chapter 6 P191-214)
15 Review
16 Review of the semester

 

Course Notes/Textbooks

Statistics for Engineers and Scientists, William Navidi, 5th Ed., Mc-Graw Hill.

Suggested Readings/Materials A First Course in Probability, S. Ross, Pearson Prentice Hall. Introduction to Probability, D.P. Bertsekas, J.N. Tsitsiklis, Athena Scientific Applied Statistics and Probability for Engineers, Douglas C. Montgomery & George C. Runger, 5th Ed., John Wiley & Sons, Inc

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm
2
60
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
2
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
Study Hours Out of Class
16
3
Field Work
Quizzes / Studio Critiques
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
2
22
Final Exam
1
40
    Total
180

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science, Computer Science and Software Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

X
2

To be able to identify, define, formulate, and solve complex Software Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to design, implement, verify, validate, document, measure and maintain a complex software system, process, or product under realistic constraints and conditions, in such a way as to meet the requirements; ability to apply modern methods for this purpose.

X
4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in software engineering applications; to be able to use information technologies effectively.

X
5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex Software Engineering problems.

X
6

To be able to work effectively in Software Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to be able to present effectively, to be able to give and receive clear and comprehensible instructions.

8

To have knowledge about global and social impact of engineering practices and software applications on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Engineering and Software Engineering solutions.

9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.

10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Software Engineering, and to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Software Engineering.

X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest