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 | Area Elective | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Area Elective Courses (Group B) |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Question and Answer, Problem Solving. |
Course Lecturer(s) |
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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;
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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 |
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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. |
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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 |
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Percentage of Final Work | 40 |
Total | 100 |
Course Category
Core Courses | X |
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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 | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | Adequate knowledge in mathematics, science and subjects specific to the Materials Engineering; the ability to apply theoretical and practical knowledge of these areas to solve complex engineering problems and to model and solve of materials systems | X | ||||
2 | Understanding of science and engineering principles related to the structures, properties, processing and performance of Materials systems | |||||
3 | Ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose | X | ||||
4 | Ability to design and choose proper materials for a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design and materials selection methods for this purpose | |||||
5 | Ability to develop, select and utilize modern techniques and tools essential for the analysis and solution of complex problems in Materails Engineering applications; the ability to utilize information technologies effectively | X | ||||
6 | Ability to design and conduct experiments, collect data, analyse and interpret results using statistical and computational methods for complex engineering problems or research topics specific to Materials Engineering | X | ||||
7 | Ability to work effectively in inter/inner disciplinary teams; ability to work individually | |||||
8 | Effective oral and written communication skills in Turkish; knowlegde of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions | |||||
9 | Recognition of the need for lifelong learning; the ability to access information; follow recent developments in science and technology with continuous self-development | |||||
10 | Ability to behave according to ethical principles, awareness of professional and ethical responsibility; knowledge of standards used in engineering applications | |||||
11 | Knowledge on business practices such as project management, risk management and change management; awareness in entrepreneurship and innovativeness; knowledge of sustainable development | |||||
12 | Knowledge of the effects of Materials Engineering applications on the universal and social dimensions of health, environment and safety, knowledge of modern age problems reflected on engineering; awareness of legal consequences of engineering solutions |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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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 |