ECTS - Statistical Analysis and Instrumentation
Statistical Analysis and Instrumentation (MFGE312) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Statistical Analysis and Instrumentation | MFGE312 | 6. Semester | 3 | 1 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Compulsory Departmental Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Drill and Practice, Team/Group. |
Course Lecturer(s) |
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Course Objectives | This course aims to give student an experience of experimental design, measurement instrumentations and tools. In addition, data analysis types, statistical data interpretations are introduced. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Basic concepts, analysis of experimental data, working principles of basic electrical measurements and sensing devices. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Introduction to Design of experiments (DoE) | Chapter 1 |
2 | Introduction to Design of experiments (DoE) | Chapter 2 |
3 | Basic concepts: Active and passive instruments, analog and digital instruments, readability, hysteresis, calibration, standards, dimensions and units, measurement systems, etc. | Chapter 3 |
4 | 0, 1st and 2nd order measurement systems | Chapter 4 |
5 | 0, 1st and 2nd order measurement systems | Chapter 5 |
6 | Analog and digital meters, Input circuits, amplifiers, signal conditioning, output recorders, transducers | Chapter 6 |
7 | Analysis of Experimental Data: Error and uncertainty analysis, standard deviation, probability distributions, method of least squares, multivariable regression, curve fitting | Chapter 7 |
8 | Analysis of Experimental Data: Error and uncertainty analysis, standard deviation, probability distributions, method of least squares, multivariable regression, curve fitting | Chapter 8 |
9 | Analysis of Experimental Data: Error and uncertainty analysis, standard deviation, probability distributions, method of least squares, multivariable regression, curve fitting | Chapter 9 |
10 | Displacement, area, length, angle and surface roughness measurement measurement | Chapter 10 |
11 | Temperature Measurement | Chapter 11 |
12 | Temperature Measurement | Chapter 12 |
13 | Force, torque and strain measurements | Chapter 13 |
14 | Force, torque and strain measurements | Chapter 14 |
15 | Project Presentations | Chapter 15 |
16 | Final exam | All chapters |
Sources
Course Book | 1. Experimental Methods for Engineers, J.P.Holman, 8Th Ed., Mc Graw Hill |
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Other Sources | 2. Theory and Design for Mechanical Measurements, Richard S. Figliola, Donald. E. Beasley, 6th Edition, Wiley |
3. Ölçme Tekniği: Boyut, Basınç, Akış ve Sıcaklık Ölçmeleri, Prof. Dr. Osman F. Genceli, Birsen Yayınevi, 2016 |
Evaluation System
Requirements | Number | Percentage of Grade |
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Attendance/Participation | 1 | 5 |
Laboratory | 1 | 5 |
Application | - | - |
Field Work | 1 | 5 |
Special Course Internship | 1 | 5 |
Quizzes/Studio Critics | - | - |
Homework Assignments | - | - |
Presentation | 1 | 10 |
Project | 1 | 20 |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 1 | 20 |
Final Exam/Final Jury | 1 | 30 |
Toplam | 8 | 100 |
Percentage of Semester Work | 70 |
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Percentage of Final Work | 30 |
Total | 100 |
Course Category
Core Courses | |
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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 | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | An ability to apply knowledge in mathematics and basic sciences and computational skills to solve manufacturing engineering problems | X | ||||
2 | An ability to define and analyze issues related with manufacturing technologies | X | ||||
3 | An ability to develop a solution based approach and a model for an engineering problem and design and manage an experiment | X | ||||
4 | An ability to design a comprehensive manufacturing system based on creative utilization of fundamental engineering principles while fulfilling sustainability in environment and manufacturability and economic constraints | X | ||||
5 | An ability to chose and use modern technologies and engineering tools for manufacturing engineering applications | X | ||||
6 | An ability to utilize information technologies efficiently to acquire datum and analyze critically, articulate the outcome and make decision accordingly | X | ||||
7 | An ability to attain self-confidence and necessary organizational work skills to participate in multi-diciplinary and interdiciplinary teams as well as act individually | X | ||||
8 | An ability to attain efficient communication skills in Turkish and English both verbally and orally | |||||
9 | An ability to reach knowledge and to attain life-long learning and self-improvement skills, to follow recent advances in science and technology | |||||
10 | An awareness and responsibility about professional, legal, ethical and social issues in manufacturing engineering | |||||
11 | An awareness about solution focused project and risk management, enterpreneurship, innovative and sustainable development | |||||
12 | An understanding on the effects of engineering applications on health, social and legal aspects at universal and local level during decision making process |
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 | 2 | 1 | 2 |
Application | |||
Special Course Internship | |||
Field Work | 1 | 3 | 3 |
Study Hours Out of Class | 12 | 2 | 24 |
Presentation/Seminar Prepration | 1 | 4 | 4 |
Project | 1 | 30 | 30 |
Report | |||
Homework Assignments | |||
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 1 | 5 | 5 |
Prepration of Final Exams/Final Jury | 1 | 5 | 5 |
Total Workload | 121 |