ECTS - Statistical Applications in Industrial Engineering
Statistical Applications in Industrial Engineering (IE442) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Statistical Applications in Industrial Engineering | IE442 | Area Elective | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| N/A |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Demonstration, Experiment, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | The course aims to prepare the student to analyze and classify data and develop empirical models for industrial engineering problems under service/production contexts. The student will be able to distinguish between different statistical techniques and implement them using a statistical software package. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Applications of simple and multiple linear regression, design and analysis of experiments, multivariate analysis and nonparametric tests for the solution of industrial engineering problems. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Syllabus Introduction | |
| 2 | Review of Some Statistical Topics | |
| 3 | Simple Linear Regression | |
| 4 | Multiple Linear Regression | |
| 5 | Design and Analysis of Single Factor Experiments | |
| 6 | Design and Analysis of Single Factor Experiments | |
| 7 | Design of Experiments with Several Factors | |
| 8 | Design of Experiments with Several Factors | |
| 9 | Multivariate Statistical Analysis | |
| 10 | Multivariate Statistical Analysis | |
| 11 | Midterm | |
| 12 | Non-parametric Tests | |
| 13 | Non-parametric tests | |
| 14 | Case studies and Applications | |
| 15 | Final Examination Period | |
| 16 | Final Examination Period |
Sources
| Other Sources | 1. Editors, Coleman,S.,Greenfield,T.,Stewardson,D. and Montgomery,D. Statistical Practice in Business and Industry, Wiley, 2008. |
|---|---|
| 3. Montgomery, D.C., and Runger, G.C., Applied Statistics and Probability for Engineers, John Wiley and Sons, Inc., 4th Edition, June 2006. | |
| 4. Czitron,V., Spagon, P.O., Statistical case studies for industrial process improvement, SIAM,1997 | |
| 5. Ross, S. Introduction to Probability and Statistics for Engineers and Scientists, Academic Press, 3rd edition, 2004. | |
| 7. Schuyler,W. Reading Statistics and Research, Pearson,4th edition,2004. | |
| 9. Tabachnick, B.G. and Fidell, L.S.Using multivariate statistics, Pearson, 4th edition, 2001. | |
| 11. Editors, Tinsley, Howard E.A., Brown, S.D.Handbook of Applied Multivariate Statistics and mathematical modelling, Academic Press, 2000. | |
| 14. Allison, P. Multiple Regression: A primer, Pine Forge, 1999. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | 1 | 10 |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | 5 | 15 |
| Presentation | - | - |
| Project | 1 | 10 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 30 |
| Final Exam/Final Jury | 1 | 35 |
| Toplam | 9 | 100 |
| Percentage of Semester Work | 65 |
|---|---|
| Percentage of Final Work | 35 |
| Total | 100 |
Course Category
| Core Courses | |
|---|---|
| Major Area Courses | X |
| 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 | Gains adequate knowledge in mathematics, science, and relevant engineering disciplines and acquires the ability to use theoretical and applied knowledge in these fields to solve complex engineering problems. | |||||
| 2 | Gains the ability to identify, formulate, and solve complex engineering problems and the ability to select and apply appropriate analysis and modeling methods for this purpose. | X | ||||
| 3 | Gains the ability to design a complex system, process, device, or product under realistic constraints and conditions to meet specific requirements and to apply modern design methods for this purpose. | |||||
| 4 | Gains the ability to select and use modern techniques and tools necessary for the analysis and solution of complex engineering problems encountered in industrial engineering applications and the ability to use information technologies effectively. | X | ||||
| 5 | Gains the ability to design experiments, conduct experiments, collect data, analyze results, and interpret findings for investigating complex engineering problems or discipline specific research questions. | X | ||||
| 6 | Gains the ability to work effectively in intra-disciplinary and multi-disciplinary teams and the ability to work individually. | |||||
| 7 | Gains the ability to communicate effectively in written and oral form, acquires proficiency in at least one foreign language, the ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | |||||
| 8 | Gains awareness of the need for lifelong learning and the ability to access information, follow developments in science and technology, and to continue to educate him/herself. | |||||
| 9 | Gains knowledge about behaviour in accordance with ethical principles, professional and ethical responsibility and standards used in industrial engineering applications | |||||
| 10 | Gains knowledge about business practices such as project management, risk management, and change management and develops awareness of entrepreneurship, innovation, and sustainable development. | |||||
| 11 | Gains knowledge about the global and social effects of industrial engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. | |||||
| 12 | Gains skills in the design, development, implementation, and improvement of integrated systems involving human, material, information, equipment, and energy. | |||||
| 13 | Gains knowledge about appropriate analytical and experimental methods, as well as computational methods, for ensuring system integration. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 2 | 32 |
| Laboratory | |||
| Application | 16 | 1 | 16 |
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 2 | 28 |
| Presentation/Seminar Prepration | |||
| Project | 1 | 18 | 18 |
| Report | |||
| Homework Assignments | 5 | 5 | 25 |
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 3 | 3 |
| Prepration of Final Exams/Final Jury | 1 | 3 | 3 |
| Total Workload | 125 | ||