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 |
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Statistical Applications in Industrial Engineering | IE442 | 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 | Elective Courses |
Course Level | Natural & Applied Sciences Master's Degree |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Demonstration, Experiment, Problem Solving. |
Course Lecturer(s) |
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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;
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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 |
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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. |
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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 |
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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 |
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Percentage of Final Work | 35 |
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 | Having accumulated knowledge on mathematics, science and engineering and an ability to apply these knowledge to solve Civil engineering problems. | X | ||||
2 | Ability to design Cİvil Engineering systems fulfilling sustainability in environment and manufacturability and economic constraints | X | ||||
3 | An ability to differentiate, identify, formulate, and solve complex engineering problems; an ability to select and implement proper analysis, modeling and implementation techniques for the identified engineering problems. | |||||
4 | An ability to develop a solution based approach and a model for an engineering problem and design and manage an experiment | |||||
5 | Ability to use modern engineering tools, techniques and facilities in design and other engineering applications | X | ||||
6 | Ability to carry out independent research in the field and to report the results of the research effectively and be able to present the research results at scientific meetings. | |||||
7 | Sufficient oral and written English knowledge to follow scientific conferences in the field and communicate with colleagues. | X | ||||
8 | Ability to effectively use knowledge in the field to work in disciplinary/multidisciplinary teams and the skill to lead these teams | X | ||||
9 | Consciousness on the necessity of improvement and sustainability as a result of life-long learning,ability for continuous renovation and monitoring the developments on science and technology and awareness on entrepreneurship and innovation | |||||
10 | Professional and ethical responsibility to gather and interpret data, apply and announce solutions to Civil Engineering problems. | |||||
11 | An ability to investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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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 |