Course Detail
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| DESIGN of EXPERIMENT | - | Spring Semester | 3+0 | 3 | 6 |
| Course Program |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Elective |
| Course Coordinator | Assoc.Prof. Melis Almula KARADAYI |
| Name of Lecturer(s) | Assoc.Prof. Melis Almula KARADAYI |
| Assistant(s) | |
| Aim | This course aims to teach the basic principles and methods of statistical experimental design. |
| Course Content | This course contains; Review of Basic Statistical Concepts,Introduction to Design of Experiments,Comparing Multiple Means. Analysis of Variance (ANOVA),Single Factor Experiments & One-Way Analysis of Variance,One-Way Analysis of Variance. Simultaneous Confidence Intervals. Parameter Estimation.,Expected Mean Square (EMS) & Power Calculations,Special Case of Two Averages,Random Effects Model,Randomized Block Designs,Multifactor Designs,Two-Factor Experiments I,Two-Factor Experiments II,Mixed Effect Models,2k Multifactor Designs. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| 5.Use statistical package SPSS. | 13, 14, 9 | F |
| 4.Evaluate random effects and mixed effects | 12, 13, 9 | A |
| 3.Analyze the results of the experiment with Analysis of Variance (Anova) | 12, 13, 9 | A |
| 1. Collect, analyze, interpret and present data | 13, 14, 16, 9 | A |
| 2. Design Engineering Experiments | 13, 16, 9 | A |
| Teaching Methods: | 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam, F: Project Task |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Review of Basic Statistical Concepts | |
| 2 | Introduction to Design of Experiments | |
| 3 | Comparing Multiple Means. Analysis of Variance (ANOVA) | |
| 4 | Single Factor Experiments & One-Way Analysis of Variance | |
| 5 | One-Way Analysis of Variance. Simultaneous Confidence Intervals. Parameter Estimation. | |
| 6 | Expected Mean Square (EMS) & Power Calculations | |
| 7 | Special Case of Two Averages | |
| 8 | Random Effects Model | |
| 9 | Randomized Block Designs | |
| 10 | Multifactor Designs | |
| 11 | Two-Factor Experiments I | |
| 12 | Two-Factor Experiments II | |
| 13 | Mixed Effect Models | |
| 14 | 2k Multifactor Designs |
| Resources |
| Design and Analysis of Experiments, 7th Ed. D. C. Montgomery, John Wiley & Sons, 2009. |
| Probability and Statistics for Engineers and Scientists, 9th Ed. R. E. Walpole, R. H. Myers, S. L. Myers and K. Ye , Pearson Education 2012. |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | X | |||||
| 2 | Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | X | |||||
| 3 | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | ||||||
| 4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. | X | |||||
| 5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. | X | |||||
| 6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | X | |||||
| 7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | X | |||||
| 8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | ||||||
| 9 | Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices. | X | |||||
| 10 | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | ||||||
| 11 | Knowledge about the global and social effects of 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. | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 30 | |
| Rate of Final Exam to Success | 70 | |
| Total | 100 | |
| ECTS / Workload Table | ||||||
| Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
| Course Hours | 14 | 3 | 42 | |||
| Guided Problem Solving | 0 | 0 | 0 | |||
| Resolution of Homework Problems and Submission as a Report | 5 | 10 | 50 | |||
| Term Project | 1 | 30 | 30 | |||
| Presentation of Project / Seminar | 1 | 1 | 1 | |||
| Quiz | 5 | 3 | 15 | |||
| Midterm Exam | 1 | 14 | 14 | |||
| General Exam | 1 | 28 | 28 | |||
| Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
| Total Workload(Hour) | 180 | |||||
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(180/30) | 6 | |||||
| ECTS of the course: 30 hours of work is counted as 1 ECTS credit. | ||||||
Detail Informations of the Course
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| DESIGN of EXPERIMENT | - | Spring Semester | 3+0 | 3 | 6 |
| Course Program |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | First Cycle (Bachelor's Degree) |
| Course Type | Elective |
| Course Coordinator | Assoc.Prof. Melis Almula KARADAYI |
| Name of Lecturer(s) | Assoc.Prof. Melis Almula KARADAYI |
| Assistant(s) | |
| Aim | This course aims to teach the basic principles and methods of statistical experimental design. |
| Course Content | This course contains; Review of Basic Statistical Concepts,Introduction to Design of Experiments,Comparing Multiple Means. Analysis of Variance (ANOVA),Single Factor Experiments & One-Way Analysis of Variance,One-Way Analysis of Variance. Simultaneous Confidence Intervals. Parameter Estimation.,Expected Mean Square (EMS) & Power Calculations,Special Case of Two Averages,Random Effects Model,Randomized Block Designs,Multifactor Designs,Two-Factor Experiments I,Two-Factor Experiments II,Mixed Effect Models,2k Multifactor Designs. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| 5.Use statistical package SPSS. | 13, 14, 9 | F |
| 4.Evaluate random effects and mixed effects | 12, 13, 9 | A |
| 3.Analyze the results of the experiment with Analysis of Variance (Anova) | 12, 13, 9 | A |
| 1. Collect, analyze, interpret and present data | 13, 14, 16, 9 | A |
| 2. Design Engineering Experiments | 13, 16, 9 | A |
| Teaching Methods: | 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam, F: Project Task |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Review of Basic Statistical Concepts | |
| 2 | Introduction to Design of Experiments | |
| 3 | Comparing Multiple Means. Analysis of Variance (ANOVA) | |
| 4 | Single Factor Experiments & One-Way Analysis of Variance | |
| 5 | One-Way Analysis of Variance. Simultaneous Confidence Intervals. Parameter Estimation. | |
| 6 | Expected Mean Square (EMS) & Power Calculations | |
| 7 | Special Case of Two Averages | |
| 8 | Random Effects Model | |
| 9 | Randomized Block Designs | |
| 10 | Multifactor Designs | |
| 11 | Two-Factor Experiments I | |
| 12 | Two-Factor Experiments II | |
| 13 | Mixed Effect Models | |
| 14 | 2k Multifactor Designs |
| Resources |
| Design and Analysis of Experiments, 7th Ed. D. C. Montgomery, John Wiley & Sons, 2009. |
| Probability and Statistics for Engineers and Scientists, 9th Ed. R. E. Walpole, R. H. Myers, S. L. Myers and K. Ye , Pearson Education 2012. |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | X | |||||
| 2 | Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | X | |||||
| 3 | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | ||||||
| 4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. | X | |||||
| 5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. | X | |||||
| 6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | X | |||||
| 7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | X | |||||
| 8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | ||||||
| 9 | Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices. | X | |||||
| 10 | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | ||||||
| 11 | Knowledge about the global and social effects of 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. | ||||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 30 | |
| Rate of Final Exam to Success | 70 | |
| Total | 100 | |