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 |
|---|---|---|---|---|---|---|---|
| Statistical Analysis and Instrumentation | MFGE312 | Area Elective | 3 | 1 | 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, Drill and Practice, Team/Group. |
| Course Lecturer(s) |
|
| 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;
|
| 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 |
|---|---|---|
| 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 |
|---|---|
| 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 |
|---|---|---|
| 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 |
|---|---|
| Percentage of Final Work | 30 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| 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 | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Knowledge of mathematics, natural sciences, engineering fundamentals, computing, and topics specific to the relevant engineering discipline; the ability to use this knowledge in the solution of complex engineering problems. | |||||
| 2 | The ability to identify, formulate, and analyze complex engineering problems using knowledge of basic sciences, mathematics, and engineering, and considering the UN Sustainable Development Goals relevant to the problem. | |||||
| 3 | The ability to design creative solutions for complex engineering problems; the ability to design complex systems, processes, devices, or products to meet current and future requirements, considering realistic constraints and conditions. | |||||
| 4 | The ability to select and use appropriate techniques, resources, and modern engineering and IT tools, including prediction and modeling, for the analysis and solution of complex engineering problems, with an awareness of their limitations. | |||||
| 5 | The ability to use research methods for the investigation of complex engineering problems, including literature search, designing and conducting experiments, collecting data, and analyzing and interpreting results. | |||||
| 6 | Knowledge of the effects of engineering practices on society, health and safety, the economy, sustainability, and the environment within the scope of the UN Sustainable Development Goals; awareness of the legal consequences of engineering solutions. | |||||
| 7 | Acting in accordance with engineering professional principles, knowledge of ethical responsibility; awareness of acting impartially without discrimination on any grounds and being inclusive of diversity. | |||||
| 8 | The ability to work effectively individually and in intra-disciplinary and multi-disciplinary teams (face-to-face, remote, or hybrid) as a team member or leader. | |||||
| 9 | "The ability to communicate effectively orally and in writing on technical topics, considering the various differences of the target audience (such as education, language, profession). | |||||
| 10 | Knowledge of practices in business life such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation. | |||||
| 11 | The ability to engage in life-long learning, including independent and continuous learning, adapting to new and emerging technologies, and thinking inquisitively regarding technological changes. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| 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 | ||