FACULTY OF ENGINEERING
Department of Industrial Engineering
MATH 236 | 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 |
|
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Course Language |
English
|
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Course Type |
Required
|
|||||||
Course Level |
First Cycle
|
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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;
|
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. |
|
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 | Introduction to Statistics and Data Analysis and Business | Walpole R.E., Myers R. H., Myers S. L, Ye K., Probability&Statistics for Engineers and Scientists, 9th Edition. ISBN13: 9781292161365 Chapter 1, pages 21-37 |
2 | Introduction to Statistics and Data Analysis and Business | Walpole R.E., Myers R. H., Myers S. L, Ye K., Probability&Statistics for Engineers and Scientists, 9th Edition. ISBN13: 9781292161365 Chapter 1, pages 37-50 |
3 | Fundamental Sampling Distributions and Data Descriptions | Walpole R.E., Myers R. H., Myers S. L, Ye K., Probability&Statistics for Engineers and Scientists, 9th Edition. ISBN13: 9781292161365 Chapter 3,Section 3.3, pages 107-114 |
4 | Fundamental Sampling Distributions and Data Descriptions | Walpole R.E., Myers R. H., Myers S. L, Ye K., Probability&Statistics for Engineers and Scientists, 9th Edition. ISBN13: 9781292161365 Chapter 8, pages 263-282 |
5 | One- and Two-Sample Estimation Problems | Walpole R.E., Myers R. H., Myers S. L, Ye K., Probability&Statistics for Engineers and Scientists, 9th Edition. ISBN13: 9781292161365 Chapter 8, pages 263-282 |
6 | One- and Two-Sample Estimation Problems | Walpole R.E., Myers R. H., Myers S. L, Ye K., Probability&Statistics for Engineers and Scientists, 9th Edition. ISBN13: 9781292161365 Chapter 9, pages 320-327 |
7 | One- and Two-Sample Estimation Problems | Walpole R.E., Myers R. H., Myers S. L, Ye K., “One- and Two-Sample Tests of Hypotheses“ Chap. 10 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 339-362. |
8 | Midterm | |
9 | One- and Two-Sample Tests of Hypotheses | Walpole R.E., Myers R. H., Myers S. L, Ye K., “One- and Two-Sample Tests of Hypotheses“ Chap. 10 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 362-385. |
10 | One- and Two-Sample Tests of Hypotheses | Walpole R.E., Myers R. H., Myers S. L, Ye K., Probability&Statistics for Engineers and Scientists, 9th Edition. ISBN13: 9781292161365 Chapter 10, pages 386-393 |
11 | One- and Two-Sample Tests of Hypotheses | Walpole R.E., Myers R. H., Myers S. L, Ye K., “One- and Two-Sample Tests of Hypotheses“ Chap. 10 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 386-393. |
12 | One- and Two-Sample Tests of Hypotheses | Walpole R.E., Myers R. H., Myers S. L, Ye K., “One- and Two-Sample Tests of Hypotheses“ Chap. 10 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 393-396. |
13 | Two-Sample Excel Case Study | Walpole R.E., Myers R. H., Myers S. L, Ye K., “One- and Two-Sample Tests of Hypotheses“ Chap. 10 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 399. |
14 | Two-Sample Excel Case Study | Walpole R.E., Myers R. H., Myers S. L, Ye K., “One- and Two-Sample Tests of Hypotheses“ Chap. 10 Probability & Statistics for Engineers and Scientists, 9th Edition (Pearson, 2017), 399. |
15 | Semester Review | |
16 | Final Exam |
Course Notes/Textbooks | Walpole R.E., Myers R. H., Myers S. L,Ye K., |
Suggested Readings/Materials | Ross S., A First Course in Probability, Pearson Education. "Statistics for Engineers and Scientists" by William Navidi, McGraw-Hill Education, 4th Edition, 2014. ISBN-13: 978-0073401331 |
EVALUATION SYSTEM
Semester Activities | Number | Weigthing |
Participation | ||
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques |
2
|
10
|
Portfolio | ||
Homework / Assignments | ||
Presentation / Jury | ||
Project | ||
Seminar / Workshop | ||
Oral Exams | ||
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 |
---|---|---|---|
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 |
2
|
10
|
20
|
Portfolio |
0
|
||
Homework / Assignments |
0
|
||
Presentation / Jury |
0
|
||
Project |
0
|
||
Seminar / Workshop |
0
|
||
Oral Exam |
0
|
||
Midterms |
1
|
30
|
30
|
Final Exam |
1
|
40
|
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. |
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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. |
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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. |
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6 | To be able to work efficiently in Industrial Engineering disciplinary and multidisciplinary teams; to be able to work individually. |
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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 |
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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. |
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9 | To be aware of professional and ethical responsibility; to have knowledge of the standards used in Industrial Engineering practice. |
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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. |
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11 | To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language. |
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12 | To be able to speak a second foreign at a medium level of fluency efficiently. |
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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
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