FACULTY OF ARTS AND SCIENCES
Department of Mathematics
SOCIAL MEDIA
MATH 203 | Course Introduction and Application Information
| Course Name |
Introduction to Probability Theory I
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
MATH 203
|
Fall
|
2
|
2
|
3
|
6
|
| Prerequisites |
None
|
|||||
| Course Language |
English
|
|||||
| Course Type |
Required
|
|||||
| Course Level |
First Cycle
|
|||||
| Mode of Delivery | face to face | |||||
| Teaching Methods and Techniques of the Course | Problem SolvingLecture / Presentation | |||||
| Course Coordinator | - | |||||
| Course Lecturer(s) | ||||||
| Assistant(s) | ||||||
| Course Objectives | This course aims to consider basic theory and applications of probability theory including probability axioms, distribution functions, conditional probability, total probability and Bayes formula, random variables, distributions of discrete and continuous random variables and their expectations, hazard rate, and mean residual life functions. |
| Learning Outcomes |
The students who succeeded in this course;
|
| Course Description | This course aims to provide basic theory and applications of Probability Theory. |
|
|
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 | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772.Chapter 1 |
| 2 | Classical probability | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772.Chapter 1 |
| 3 | Axioms of probability | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772.Chapter 2 |
| 4 | Properties of probability | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772.Chapter 4 |
| 5 | Conditional probability and independence of events | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772. Chapter 3 |
| 6 | Total probability formula and Bayes' formula | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772. Chapter 3 |
| 7 | Random variables and properties of distribution functions, types of random variables, some discrete random variables | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772. Chapter 4 |
| 8 | Midterm | |
| 9 | Some continuous random variables | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772. Chapter 5 |
| 10 | Expected value | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772.Chapter 4 |
| 11 | Expectation of a function of a random variable | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772.Chapters 4 & 5 |
| 12 | Variance | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772.Chapters 4 & 5 |
| 13 | Hazard rate functions | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772.5 Chapter 5 |
| 14 | The wellknown distribution functions, mean residual life function | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772.Chapters 4 & 5 |
| 15 | Semester review | |
| 16 | Final exam |
| Course Notes/Textbooks | Sheldon Ross,''A First Course in Probability'' 9th edition,Pearson,2012. ISBN-13: 978-0321794772. |
| Suggested Readings/Materials | Ronald Walpole, Raymond Myers, Sharon Myer. “Probability and Statistics for Engineers and Scientists”, Publisher:Pearson; 9 edition,2010.ISBN-13: 978-0321629111 |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques |
1
|
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 |
2
|
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
|
2
|
32
|
| Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
2
|
32
|
| Study Hours Out of Class |
14
|
3
|
42
|
| Field Work |
0
|
||
| Quizzes / Studio Critiques |
1
|
15
|
15
|
| Portfolio |
0
|
||
| Homework / Assignments |
0
|
||
| Presentation / Jury |
0
|
||
| Project |
0
|
||
| Seminar / Workshop |
0
|
||
| Oral Exam |
0
|
||
| Midterms |
1
|
25
|
25
|
| Final Exam |
1
|
34
|
34
|
| 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. |
|||||
| 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. |
|||||
| 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. |
X | ||||
| 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. |
|||||
| 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. |
|||||
| 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. |
|||||
| 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. |
|||||
| 11 | To be able to collect data in the areas of Mathematics or Statistics and 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 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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