ECTS - Probability and Statistics II
Probability and Statistics II (IE202) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Probability and Statistics II | IE202 | 3 | 1 | 0 | 3 | 6.5 |
Pre-requisite Course(s) |
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IE 201 |
Course Language | English |
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Course Type | N/A |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Discussion, Question and Answer, Problem Solving, Team/Group, Project Design/Management. |
Course Lecturer(s) |
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Course Objectives | The course aims to expose students to basic concepts of statistical inference, linear regression and correlation, forecasting and experimental design. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Sampling distributions, point estimation, confidence intervals and interval estimation, hypothesis testing, simple linear regression and correlation, multiple linear regression, analysis of variance with a single factor |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Fundamentals of Sampling Distributions and Data Descriptions | [1] pages 224-244 |
2 | One-and-two-sample estimation problems | [1] pages 253-276 |
3 | One-and-two-sample estimation problems | [1] pages 253-276 |
4 | One-and-two-sample estimation problems | [1] pages 253-276 |
5 | One-and-two-sample tests of hypotheses | [1] pages 283-344 |
6 | One-and-two-sample tests of hypotheses | [1] pages 283-344 |
7 | One-and-two-sample tests of hypotheses | [1] pages 283-344 |
8 | Midterm I | |
9 | Simple Linear Regression | [1] pages 401-440 |
10 | Simple Linear Regression | [1] pages 401-440 |
11 | ANOVA and its applications | [1] pages 449-502 |
12 | Multiple Linear Regression | [1] pages 449-502 |
13 | Midterm II | |
14 | Design of Experiments | [1] pages 514-544 |
15 | Industrial Engineering Topics: Forecasting, Quality and Simulation Applications | |
16 | Industrial Engineering Topics: Forecasting, Quality and Simulation Applications |
Sources
Course Book | 1. Montgomery, D.C., and Runger, G.C., Applied Statistics and Probability for Engineers, 5th Edition, John Wiley and Sons, 2011. |
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Other Sources | 2. Walpole, R.E., Myers, R.H., Myers, S.L. and Ye, K., Probability and Statistics for Engineers and Scientists, Prentice Hall, 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. | |
6. Hines, W.W. and Montgomery, D.A., Probability and Statistics in Engineering and Management Science, John Wiley, 1990. | |
7. Navidi,W. Statistics for Engineers and Scientists, McGraw-Hill, 2008. | |
8. Mendenhall, W. and Sincich, T. Statistics for Engineering and the Sciences. Prentice Hall, 2007. |
Evaluation System
Requirements | Number | Percentage of Grade |
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Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | 1 | 10 |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | 3 | 15 |
Presentation | - | - |
Project | 1 | 15 |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 2 | 40 |
Final Exam/Final Jury | 1 | 20 |
Toplam | 8 | 100 |
Percentage of Semester Work | 80 |
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Percentage of Final Work | 20 |
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 | An ability to apply knowledge of mathematics, science and engineering to Industrial Engineering; an ability to apply theoretical and practical knowledge to model and solve engineering problems. | X | ||||
2 | An ability to identify, formulate and solve complex engineering problems; an ability to select and apply proper analysis and modeling methods. | X | ||||
3 | An ability to design a complex system, process, tool or component to meet desired needs within realistic constraints; an ability to apply modern design. | |||||
4 | An ability to develop, select and put into practice techniques, skills and modern engineering tools necessary for engineering practice; an ability to use information technology effectively. | X | ||||
5 | An ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or disciplinary research topics. | X | ||||
6 | An ability to work individually, on teams, and/or on multidisciplinary teams. | |||||
7 | Ability to communicate effectively in Turkish orally and in writing; knowledge of at least one foreign language; effective report writing and understand written reports, preparing design and production reports, making effective presentations, giving and receiving clear and understandable instruction. | |||||
8 | A recognition of the need for, and an ability to engage in life-long learning; an ability to use information-seeking tools and to follow the improvements in science and technology. | |||||
9 | An ability to behave according to the ethical principles, an understanding of professional and ethical responsibility. Information on standards used in industrial engineering applications. | |||||
10 | Knowledge of business applications such as project management, risk management and change management. A recognition of entrepreneurship, innovativeness. Knowledge of sustainable improvement. | |||||
11 | Information on the effects of industrial engineering practices on health, environment and security in universal and societal dimensions and the information on the problems of the in the field of engineering of the era. Awareness of the legal consequences of engineering solutions. | |||||
12 | An ability to design, development, implementation and improvement of integrated systems that include human, materials, information, equipment and energy. | |||||
13 | Knowlede on appropriate analytical, computational and experimental methods to provide system integration. |
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 | 14 | 2 | 28 |
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 16 | 2 | 32 |
Presentation/Seminar Prepration | |||
Project | 1 | 15 | 15 |
Report | |||
Homework Assignments | 3 | 6 | 18 |
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 1 | 10 | 10 |
Prepration of Final Exams/Final Jury | 1 | 12 | 12 |
Total Workload | 163 |