DEPARTMENT OF INDUSTRIAL ENGINEERING (ENGLISH)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

1400211013

Ders İsmi:

Probability and Statistics

Ders Yarıyılı:

Fall

Ders Kredileri:

Theoretical	Practical	Credit	ECTS
3	0	3	6

Language of instruction:

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Necessary

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Assoc. Prof. Esengül SALTÜRK

Course Lecturer(s):

Assoc. Prof. Esengül SALTÜRK

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:

The aim of the course is to introduce students the basic principals of probability and statistics so that the students should use them in engineering applications such as machine learning, artificial intelligence, computer graphics, randomized algorithms and image processing etc.

Course Content:

Foundations of Probability. Sample spaces, probabilities and distributions, discrete and continuous random variables, expectation, joint probabilities and independence.
Limit Theorems. Law of large numbers, central limit theorem.
Basic Statistics. Mean, variance, covariance, correlation.
Regression. Linear models, least squares estimation.
Hypothesis Testing. Null hypothesis, test statistics, type I and II errors, t-tests.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Understand the language and core concepts of probability theory including combinatorics, independence, conditional probability and Bayes' Theorem.
2) Learn the basic principles of statistical inference.
3) Understand the connection between probability and statistics.
2 - Skills
Cognitive - Practical
1) Use common discrete and continuous probability functions.
2) Learn confidence intervals and perform statistical inference such as hypothesis testing and regression.
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Introduction. Sample Spaces. Events. Probability.	Chapter 1
2)	Conditional Probability. Total Probability. Independence. Bayes' Rule.	Chapter 1
3)	Discrete Random Variables. Distributions.	Chapter 2
4)	Discrete Random Variables and Distributions	Chapter 2
5)	Continuous Random Variables and Distributions	Chapter 2
6)	Continuous Random Variables and Distributions	Chapter 2
7)	Expectation. Variance.	Chapter 3
8)	Midterm Exam
9)	Covariance and Correlation.	Chapter 3
10)	Sampling Distributions and Limits	Chapter 4
11)	Statistical Inference.	Chapter 5
12)	Estimation and Bias. Confidence Intervals.	Chapter 6
13)	Bayesian Inference. Hypothesis Testing.	Chapter 7
14)	Linear Regression.	Chapter 10
15)	Linear Regression. Review	Chapter 10
16)	Final Exam

Sources

Course Notes / Textbooks:	1. (Textbook) Probability and Statistics - The Science of Uncertainty, M.J. Evans and J.S. Rosenthal, W. H. Freeman; Second edition, 2023. 2. Applied Statistics and Probability for Engineers, Fifth Edition, Douglas C. Montgomery, George C. Runger, 2011. ISBN-13: 978-0-47005-304-1. 3. For Programming Language: Python for Probability, Statistics and Machine Learning, Jose Unpingco, Springer, 2016.
References:	1. (Textbook) Probability and Statistics - The Science of Uncertainty, M.J. Evans and J.S. Rosenthal, W. H. Freeman; Second edition, 2023. 2. Applied Statistics and Probability for Engineers, Fifth Edition, Douglas C. Montgomery, George C. Runger, 2011. ISBN-13: 978-0-47005-304-1. 3. For Programming Language: Python for Probability, Statistics and Machine Learning, Jose Unpingco, Springer, 2016.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	3	5	2	4
Program Outcomes
1) Adequate knowledge of mathematics (a), science (b) and industrial engineering (c) (1) and the ability to use this knowledge in complex engineering problems.
2) Ability to work effectively both individually and in interdisciplinary and multidisciplinary teams.
3) Awareness of the necessity of lifelong learning and the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
4) Knowledge of project management, risk management, innovation and change management, entrepreneurship and sustainable development
5) Awareness of the sectors and the ability to prepare a business plan.
6) Professional and ethical responsibility awareness and acting in accordance with ethical principles.
7) Information about the problems of the age in the field of engineering and the effects and legal consequences of engineering practices on health, environment and safety in universal and social dimensions.
8) Information about current engineering practices and standards used in engineering practices.
9) The ability to identify, formulate and solve complex engineering problems, and the ability to select and apply appropriate analysis and modeling methods for this purpose.
10) The ability to design a complex system, process, device or product using modern methods under realistic constraints and conditions and to meet specific requirements.
11) The ability to develop, select and use modern techniques and tools necessary for the solution of engineering problems, and the ability to use information technologies effectively.
12) Ability to design and conduct experiments, collect data, analyze data and interpret results for the study of engineering problems or research issues.
13) Ability to communicate effectively, write reports and make presentations in Turkish and English with oral, written and visual methods.
14) In-depth knowledge of appropriate analytical and experimental methods and computational methods for system integration such as simulation (a), production systems (b) operations research (c) and statistics (d).
15) Skills in designing (a) and improving (b), defining goals and criteria (c), analyzing (d) and developing solutions (e) systems that include people, materials, information, equipment and energy to creatively solve real-life problems

Ders - Öğrenme Kazanımı İlişkisi

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Adequate knowledge of mathematics (a), science (b) and industrial engineering (c) (1) and the ability to use this knowledge in complex engineering problems.	5
2)	Ability to work effectively both individually and in interdisciplinary and multidisciplinary teams.
3)	Awareness of the necessity of lifelong learning and the ability to access information, to follow developments in science and technology, and to constantly renew oneself.
4)	Knowledge of project management, risk management, innovation and change management, entrepreneurship and sustainable development
5)	Awareness of the sectors and the ability to prepare a business plan.
6)	Professional and ethical responsibility awareness and acting in accordance with ethical principles.
7)	Information about the problems of the age in the field of engineering and the effects and legal consequences of engineering practices on health, environment and safety in universal and social dimensions.
8)	Information about current engineering practices and standards used in engineering practices.
9)	The ability to identify, formulate and solve complex engineering problems, and the ability to select and apply appropriate analysis and modeling methods for this purpose.
10)	The ability to design a complex system, process, device or product using modern methods under realistic constraints and conditions and to meet specific requirements.	5
11)	The ability to develop, select and use modern techniques and tools necessary for the solution of engineering problems, and the ability to use information technologies effectively.
12)	Ability to design and conduct experiments, collect data, analyze data and interpret results for the study of engineering problems or research issues.	3
13)	Ability to communicate effectively, write reports and make presentations in Turkish and English with oral, written and visual methods.
14)	In-depth knowledge of appropriate analytical and experimental methods and computational methods for system integration such as simulation (a), production systems (b) operations research (c) and statistics (d).
15)	Skills in designing (a) and improving (b), defining goals and criteria (c), analyzing (d) and developing solutions (e) systems that include people, materials, information, equipment and energy to creatively solve real-life problems	3

Öğrenme Etkinliği ve Öğretme Yöntemleri

Alan Çalışması
Anlatım
Bireysel çalışma ve ödevi

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	2	% 10
Midterms	1	% 30
Semester Final Exam	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	15	3	45
Study Hours Out of Class	20	6	120
Midterms	2	5	10
Final	1	3	3
Total Workload			178