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 3 1 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type N/A
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Drill and Practice, Team/Group.
Course Coordinator
Course Lecturer(s)
  • Asst. Prof. Dr. C. Merih Şengönül
Course Assistants
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;
  • Student is expected to attain adequate knowledge of statistical analysis methods for data interpretation
  • Student is expected to attain notion of experimental design
  • Student is expected to learn how to evaluate uncertainity and bias in measurements
  • Student will learn 0, 1st and 2nd order measurement systems
  • Student will have experience on micrometers, callipper, comparators, surface roughness measument and calibration
  • Student is expected to design an experimental setup for thermocouple and strain gages for temperature and stress measurements
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
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 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 X
9 An ability to reach knowledge and to attain life-long learning and self-improvement skills, to follow recent advances in science and technology X
10 An awareness and responsibility about professional, legal, ethical and social issues in manufacturing engineering X
11 An awareness about solution focused project and risk management, enterpreneurship, innovative and sustainable development X
12 An understanding on the effects of engineering applications on health, social and legal aspects at universal and local level during decision making process X

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