FACULTY OF ARTS AND SCIENCES
Department of Mathematics
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/Spring
|
3
|
0
|
3
|
6
|
Prerequisites |
|
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Course Language |
English
|
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Course Type |
Service Course
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|||||||
Course Level |
First Cycle
|
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Mode of Delivery | face to face | |||||||
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;
|
Course Description | In this course some important theorems about probability are investigated. In addition, applications of random variables and their probability distributions are discussed. |
|
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 | Midterm | |
9 | Joint probability distributions | 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), 114-124. |
10 | Mean and Variance of a Random variable | 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), 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 |
2
|
10
|
Portfolio | ||
Homework / Assignments | ||
Presentation / Jury | ||
Project | ||
Seminar / Workshop | ||
Oral Exams | ||
Midterm |
1
|
40
|
Final Exam |
1
|
50
|
Total |
Weighting of Semester Activities on the Final Grade |
3
|
50
|
Weighting of End-of-Semester Activities on the Final Grade |
1
|
50
|
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 |
2
|
10
|
20
|
Portfolio |
0
|
||
Homework / Assignments |
0
|
||
Presentation / Jury |
0
|
||
Project |
0
|
||
Seminar / Workshop |
0
|
||
Oral Exam |
0
|
||
Midterms |
1
|
30
|
30
|
Final Exam |
1
|
40
|
40
|
Total |
180
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
#
|
Program Competencies/Outcomes |
* Contribution Level
|
||||
1
|
2
|
3
|
4
|
5
|
||
1 | To be able to have a grasp of basic mathematics, applied mathematics or theories and applications of statistics. |
X | ||||
2 | To be able to use advanced theoretical and applied knowledge, interpret and evaluate data, define and analyze problems, develop solutions based on research and proofs by using acquired advanced knowledge and skills within the fields of mathematics or statistics. |
X | ||||
3 | To be able to apply mathematics or statistics in real life phenomena with interdisciplinary approach and discover their potentials. |
X | ||||
4 | To be able to evaluate the knowledge and skills acquired at an advanced level in the field with a critical approach and develop positive attitude towards lifelong learning. |
X | ||||
5 | To be able to share the ideas and solution proposals to problems on issues in the field with professionals, non-professionals. |
X | ||||
6 | To be able to take responsibility both as a team member or individual in order to solve unexpected complex problems faced within the implementations in the field, planning and managing activities towards the development of subordinates in the framework of a project. |
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7 | To be able to use informatics and communication technologies with at least a minimum level of European Computer Driving License Advanced Level software knowledge. |
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8 | To be able to act in accordance with social, scientific, cultural and ethical values on the stages of gathering, implementation and release of the results of data related to the field. |
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9 | To be able to possess sufficient consciousness about the issues of universality of social rights, social justice, quality, cultural values and also environmental protection, worker's health and security. |
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10 | To be able to connect concrete events and transfer solutions, collect data, analyze and interpret results using scientific methods and having a way of abstract thinking. |
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11 | To be able to collect data in the areas of Mathematics or Statistics and communicate with colleagues in a foreign language. |
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12 | To be able to speak a second foreign language at a medium level of fluency efficiently. |
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13 | To be able to relate the knowledge accumulated throughout the human history to their field of expertise. |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
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