FACULTY OF ENGINEERING

Department of Industrial Engineering

MATH 336 | Course Introduction and Application Information

Course Name
Engineering Statistics II
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
MATH 336
Fall
3
0
3
5

Prerequisites
  MATH 236 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Required
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Problem Solving
Lecture / Presentation
Field work/Application
Course Coordinator -
Course Lecturer(s)
Assistant(s)
Course Objectives The main aim of the course is to introduce advanced statistical methods and usage areas to students.
Learning Outcomes The students who succeeded in this course;
  • will be able to determine appropriate distribution for the observed data.
  • will be able to analyze independence and homogeneity relationships between criteria.
  • will be able to model linear and nonlinear relationships between variables.
  • will be able to make complex models of multivariate.
  • will be able to observe the effect of one or more factors and the use of different models.
  • will be able to apply statistical methods in different fields.
Course Description Chi-square distribution and applications, goodness of fit test, simple linear regression and correlation analysis, multiple regression analysis, non-linear regression analysis, defining model in multiple regression, single and multi-factor analysis of variance.

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Tests of chi-square "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 9
2 Independence and Homogeneity Tests "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 9
3 Testing for goodness of fit "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 9
4 Introduction to regression "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 11
5 Analysis of simple regression and correlation "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 11
6 Analysis of multiple linear regression "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 12
7 Analysis of multiple linear regression "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 12
8 Methods used for defining multiple regression "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 12
9 Midterm
10 Analysis of non-linear regression "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 11
11 Analysis of variance "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 13
12 Multi-factor analysis of variance "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 13
13 The models of two-factor analysis of variance "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 14
14 Two- factor analysis of variance "Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712 Chapter 14
15 Semester Review
16 Final Exam

 

Course Notes/Textbooks

"Applied Statistics and Probability for Engineers" by D.C. Montgomery, G.C. Runger, Wiley, 6th Edition, 2013. ISBN-13: 978-1118539712

Suggested Readings/Materials

"Statistics for Engineers and Scientists" by William Navidi, McGraw-Hill Education, 4th Edition, 2014. ISBN-13: 978-0073401331

PowerPoint slides, Excel sheets supplied in lectures for example problems.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
5
25
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm
1
35
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
6
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
14
3
42
Field Work
0
Quizzes / Studio Critiques
5
4
20
Portfolio
0
Homework / Assignments
0
Presentation / Jury
0
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
15
15
Final Exam
1
25
25
    Total
150

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Industrial Engineering; to be able to use theoretical and applied information in these areas to model and solve Industrial Engineering problems.

X
2

To be able to identify, formulate and solve complex Industrial Engineering problems by using state-of-the-art methods, techniques and equipment; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to analyze a complex system, process, device or product, and to design with realistic limitations to meet the requirements using modern design techniques.

4

To be able to choose and use the required modern techniques and tools for Industrial Engineering applications; to be able to use information technologies efficiently.

X
5

To be able to design and do simulation and/or experiment, collect and analyze data and interpret the results for investigating Industrial Engineering problems and Industrial Engineering related research areas.

6

To be able to work efficiently in Industrial Engineering disciplinary and multidisciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively; to be able to give and receive clear and comprehensible instructions

8

To have knowledge about contemporary issues and the global and societal effects of Industrial Engineering practices on health, environment, and safety; to be aware of the legal consequences of Industrial Engineering solutions.

9

To be aware of professional and ethical responsibility; to have knowledge of the standards used in Industrial Engineering practice.

10

To have knowledge about business life practices such as project management, risk management, and change management; to be aware of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Industrial Engineering.

X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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