ECTS - Probability and Statistics
Probability and Statistics (IE220) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Probability and Statistics | IE220 | 4. Semester | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Compulsory Departmental Courses |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Question and Answer, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | In this course, the students will be learning fundamental concepts of the probability and statistics so that they can solve practical problems of engineering which requires statistical techniques. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Introduction to probability and statistics; random variables and probability distributions; expected value; sampling distributions; one and two sample estimation problems; test of hypotheses; simple linear regression. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | The role of probability and statistics in engineering | [1] pages 1-15 |
| 2 | Descriptive Statistics-Numerical Summary | [1] pages 191-214 |
| 3 | Descriptive Statistics-Graphical Summary | [1] pages 191-214 |
| 4 | Probability | [1] pages 17-57 |
| 5 | Probability | [1] pages 17-57 |
| 6 | Random Variables | [1] pages 67-74 [1] pages 108-114 |
| 7 | Midterm 1 | |
| 8 | Discrete Probability Distributions | [1] pages 79-97 |
| 9 | Continuous Probability Distributions | [1] pages 116-127 |
| 10 | Sampling Distributions | [1] pages 223-231 |
| 11 | Point and Interval Estimation | [1] pages 253-263 |
| 12 | Point and Interval Estimation | [1] pages 253-263 |
| 13 | Hypothesis Testing | [1] pages 283-314 |
| 14 | Midterm 2 | |
| 15 | Inference for two samples | [1] pages 351-368 |
| 16 | Simple Linear Regression | [1] pages 401-440 |
Sources
| Course Book | 1. Montgomery, D.C., and Runger, G.C., Applied Statistics and Probability for Engineers, John Wiley and Sons, Inc., 4th Edition, June 2006. |
|---|---|
| Other Sources | 2. Walpole, R.E. , Myers, R.H., Myers, S.L. an Ye, K., Probability and Statistics for Engineers and Scientists, Prentice Hall, 8th edition, 2007. |
| 3. Milton, J.S. and Arnold, J.C., Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences, McGraw-Hill, 4th edition, 2002. | |
| 4. Ross, S., Introduction to Probability and Statistics for Engineers and Scientists, Academic Press, 3rd edition, 2004. | |
| 5. Triola, M.F., Essentials of Statistics, Addison Wesley,2nd edition, 2004. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 4 | 20 |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 40 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 7 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| 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 | An ability to apply advanced knowledge of computing and/or informatics to solve software engineering problems. | |||||
| 2 | Develop solutions using different technologies, software architectures and life-cycle approaches. | |||||
| 3 | An ability to design, implement and evaluate a software system, component, process or program by using modern techniques and engineering tools required for software engineering practices. | |||||
| 4 | An ability to gather/acquire, analyze, interpret data and make decisions to understand software requirements. | |||||
| 5 | Skills of effective oral and written communication and critical thinking about a wide range of issues arising in the context of working constructively on software projects. | |||||
| 6 | 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. | |||||
| 7 | An understanding of professional, legal, ethical and social issues and responsibilities related to Software Engineering. | |||||
| 8 | 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. | |||||
| 9 | An understanding about the impact of Software Engineering solutions in a global, environmental, societal and legal context while making decisions. | |||||
| 10 | 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 | 3 | 48 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | 4 | 5 | 20 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 3 | 6 |
| Prepration of Final Exams/Final Jury | 1 | 3 | 3 |
| Total Workload | 125 | ||