COURSE INTRODUCTION AND APPLICATION INFORMATION


Course Name
Engineering Statistics
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
MATH 236
Fall/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
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Lecturing / 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.
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 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 Review of Probability and Continuous Probability Distributions, Uniform and Normal Distributions 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 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
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., Probability&Statistics for Engineers and Scientists, 9th Edition. ISBN13: 9781292161365 Chapter 9, pages 320-327
8 Midterm I
9 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
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., Probability&Statistics for Engineers and Scientists, 9th Edition. ISBN13: 9781292161365 Chapter 10, pages 393-396
12 Midterm II
13 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 393-396
14 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 393-396
15 Semester Review
16 Final Exam
Course Notes/Textbooks

Walpole R.E., Myers R. H., Myers S. L,Ye K.,
Probability&Statistics for Engineers and Scientists, 9th Edition.
ISBN13: 9781292161365

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
20
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm
1
30
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 Being able to transfer knowledge and skills acquired in mathematics and science into engineering,
2 Being able to identify and solve problem areas related to Food Engineering,
3 Being able to design projects and production systems related to Food Engineering, gather data, analyze them and utilize their outcomes in practice,
4

Having the necessary skills to develop  and use  novel technologies and equipment in the field of food engineering,

5

Being able to take part actively in team work, express his/her ideas freely, make efficient decisions as well as working individually,

6

Being able to follow universal developments and innovations, improve himself/herself continuously and have an awareness to enhance the quality,

7

Having professional and ethical awareness,

8 Being aware of universal issues such as environment, health, occupational safety in solving problems related to Food Engineering,
9

Being able to apply entrepreneurship, innovativeness and sustainability in the profession,

10

Being able to use software programs in Food Engineering and have the necessary knowledge and skills to use information and communication technologies that may be encountered in practice (European Computer Driving License, Advanced Level),

11

Being able to gather information about food engineering and communicate with colleagues using a foreign language ("European Language Portfolio Global Scale", Level B1)

12

Being able to speak a second foreign language at intermediate level.

13

Being able to relate the knowledge accumulated during the history of humanity to the field of expertise

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