FACULTY OF ENGINEERING

Department of Computer Engineering

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
Fall
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
Mode of Delivery -
Teaching Methods and Techniques of the Course Lecture / Presentation
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.
Learning Outcomes The students who succeeded in this course;
  • use fundamental concepts such as sample space, events and counting techniques.
  • explain concepts of probability.
  • use conditional probability, the total probability rule and Bayes' theorem.
  • compute discrete and continuous random variables.
  • investigate the advantages of joint probability distributions.
  • find mean and variance of random variables.
  • apply discrete and continuous distributions.
Course Description 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
X
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Sample space and events Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Probability”, Chap. 2 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 55-63.
2 Events and counting sample points Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Probability”, Chap. 2 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 58-71.
3 Counting sample points, probability of an event and additive rules Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Probability”, Chap. 2 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 64-79.
4 Additive rules, conditional probability of an event Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Probability”, Chap. 2 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 76-89.
5 Bayes’ rule Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Probability”, Chap. 2 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 92-97.
6 Concept of random variable and discrete probability distributions Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Random Variables and Probability Distributions”, Chap. 3 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 101-106.
7 Discrete probability distributions and continuous probability distributions Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Random Variables and Probability Distributions”, Chap. 3 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 104-111.
8 Joint probability distributions Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Random Variables and Probability Distributions”, Chap. 3 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 114-124.
9 Midterm
10 Mean and Variance of a Random variable Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Mathematical Expectation”, Chap. 4 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 131-147.
11 Binomial and Multinomial Distributions Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Some Discrete Probability Distributions”, Chap. 5 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 163-170.
12 Binomial and Multinomial Distributions Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Some Discrete Probability Distributions”, Chap. 5 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 172-184.
13 Uniform, Normal, Areas under the Normal Curve, Applications of the Normal dist. And Exponential distribution Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Some Continuous Probability Distributions”, Chap. 6 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 191-205.
14 Uniform, Normal, Areas under the Normal Curve, Applications of the Normal dist. And Exponential distribution Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, “Some Continuous Probability Distributions”, Chap. 6 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 191-205.
15 Semester review
16 Final Exam

 

Course Notes/Textbooks

Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, Probability and Statistics for Engineers and Scientists, 9th Edition (United States of America: Pearson, 2017).

ISBN-13: 978-0134115856

Suggested Readings/Materials

William Navidi, Statistics for Engineers and Scientists, 5th Ed. (Mc-Graw Hill, 2019)  ISBN-13: 978-1260547887

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
4
20
Portfolio
Homework / Assignments
1
20
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm
1
20
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
6
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
0
Study Hours Out of Class
14
3
42
Field Work
0
Quizzes / Studio Critiques
4
2
8
Portfolio
0
Homework / Assignments
1
12
12
Presentation / Jury
0
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
26
26
Final Exam
1
44
44
    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 and Computer 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 Computer Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Computer 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 engineering problems or Computer Engineering research topics.

6

To be able to work efficiently in Computer 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 present effectively, to be able to give and receive clear and comprehensible instructions.

8

To have knowledge about global and social impact of Computer Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Computer 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 Computer Engineering, and to be able to communicate with colleagues in a foreign language. ("European Language Portfolio Global Scale", Level B1)

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 Computer Engineering.

X

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

 


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