COURSE INTRODUCTION AND APPLICATION INFORMATION


Course Name
Engineering Statistics
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
MATH 236
Spring
3
0
3
6
Prerequisites
 MATH 154To attend the classes (To enrol for the course and get a grade other than NA or W)
Course Language
English
Course Type
Required
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Lecture / Presentation
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives This course aims to provide students with the skills to collect, analyze and interpret statistical data.
Learning Outcomes The students who succeeded in this course;
  • analyze data via graphical and quantitative means.
  • define the fundamentals of statistical decision making.
  • use basic tools for the analysis and modeling of empirical relationships between variables.
  • investigate one and two sample estimation problems.
  • use hypothesis testings.
  • identify the dependent and the independent variables of the given data.
  • test whether the given variables are related depending on the number of independent variables.
  • apply simple linear regression analysis.
Course Description This course focuses on sampling distributions, statistical estimation, hypothesis testing, simple and multiple linear regression. In addition, experimental design and applications of these methods to industrial systems engineering are discussed.
Related Sustainable Development Goals

 



Course Category

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

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Introduction to Statistics and Data Analysis and Business Douglas C. Montgomery, Geroge C. Runger, “The Role of Statistics in Engineering”, Chap. 1 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 1-10.
2 Introduction to Statistics and Data Analysis and Business, Data Description Douglas C. Montgomery, Geroge C. Runger, “Descriptive Statistics”, Chap. 6 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 198-218.
3 Fundamental Sampling Distributions and Methods of Point Estimation Douglas C. Montgomery, Geroge C. Runger, “Point Estimation of Parameters and Sampling Distributions”, Chap. 7 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 235-258.
4 Fundamental Sampling Distributions and Methods of Point Estimation Douglas C. Montgomery, Geroge C. Runger, “Point Estimation of Parameters and Sampling Distributions”, Chap. 7 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 235-258.
5 One-Sample Estimation Problems Douglas C. Montgomery, Geroge C. Runger, “Statistical Intervals for a Single Sample”, Chap. 8 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 267-287.
6 One-Sample Estimation Problems Douglas C. Montgomery, Geroge C. Runger, “Statistical Intervals for a Single Sample”, Chap. 8 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 267-287.
7 One-Sample Tests of Hypotheses Douglas C. Montgomery, Geroge C. Runger, “Tests of Hypotheses for a Single Sample”, Chap. 9 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 301-352.
8 Two-Sample Estimation Problems Douglas C. Montgomery, Geroge C. Runger, “Statistical Inference for Two Samples”, Chap. 10 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 369-385.
9 Midterm Exam
10 Two-Sample Estimation Problems Douglas C. Montgomery, Geroge C. Runger, “Statistical Inference for Two Samples”, Chap. 10 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 389-402.
11 Two-Sample Tests of Hypotheses and Two-Sample Tests of Hypotheses Douglas C. Montgomery, Geroge C. Runger, “Tests of Hypotheses for Two Samples”, Chap. 10 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 301-352.
12 Simple Linear Regression Douglas C. Montgomery, Geroge C. Runger, “Simple Linear Regression and Correlation”, Chap. 11 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 419-432.
13 Hypothesis Tests in Simple Linear Regression, Confidence Intervals Douglas C. Montgomery, Geroge C. Runger, “Simple Linear Regression and Correlation”, Chap. 11 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 432-434.
14 Coefficient of Determination Douglas C. Montgomery, Geroge C. Runger, “Simple Linear Regression and Correlation”, Chap. 11 Applied Statistics and Probability for Engineers, 7th Edition (United States of America: Wiley, 2018), 437-438.
15 Semester Review
16 Final Exam
Course Notes/Textbooks

Douglas C. Montgomery, Geroge C. Runger, Applied Statistics and Probability for Engineers, 7th Ed. (United States of America: Wiley, 2018).

ISBN: 978-1-119-40036-3

Suggested Readings/Materials

Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying Ye, Probability and Statistics for Engineers and Scientists, 9th Ed. (United States of America: Pearson, 2017).

ISBN-13: 978-0321629111

 

William Navidi, Statistics for Engineers and Scientists, 5th Ed. (United States of America: Mc-Graw Hill, 2019) 

ISBN-13: 978-1260547887

 

EVALUATION SYSTEM

Semester Activities Number Weighting
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
2
10
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm
1
40
Final Exam
1
50
Total

Weighting of Semester Activities on the Final Grade
3
50
Weighting of End-of-Semester Activities on the Final Grade
1
50
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
Study Hours Out of Class
14
3
42
Field Work
Quizzes / Studio Critiques
2
10
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
1
30
Final Exams
1
40
    Total
180

 

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.

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.

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