FACULTY OF ENGINEERING

Department of Genetics and Bioengineering

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
  MATH 154 To 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.
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.

 



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 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 Midterm
9 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.
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 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 Genetics and Bioengineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

X
2

To be able to identify, define, formulate, and solve complex Genetics and Bioengineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Genetics and Bioengineering applications; to be able to use information technologies effectively.

X
5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Genetics and Bioengineering research topics.

6

To be able to work efficiently in Genetics and Bioengineering disciplinary and multi-disciplinary 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 global and social impact of Genetics and Bioengineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Genetics and Bioengineering solutions.

9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in Genetics and Bioengineering applications.

10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Genetics and Bioengineering, and to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign language 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 Genetics and Bioengineering.

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

 


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