Computer Engineering (English) Preview
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code:

MATH210

Course Name:

Probability and Statistics

Semester:

Spring

Course Credits:

ECTS

Language of instruction:

English

Course Condition:

Does the Course Require Work Experience?:

Type of course:

Compulsory Courses

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:

Dr. Öğr. Üy. FUNDA ÖZDEMİR

Course Lecturer(s):

Assist. Prof. Dr. FUNDA ÖZDEMIR

Course Assistants:

Course Objective and Content

Course Objectives:	To teach the concepts and ideas about statistics and probability, to establish meaningful relationships between these concepts and ideas, to develop statistical thinking and reasoning skills.
Course Content:	Sample space, probability, conditional probability, counting, combinatorics, discrete/continuous random variables, conditioning, independence, expectation, variance, covariance, Bayesian inference, sampling distributions, hypothesis testing, confidence intervals, and linear regression.

Learning Outcomes

The students who have succeeded in this course;
1) Understand and apply basic concepts of probability (sample spaces, counting, etc.), the mathematical descriptions of random variables and distribution functions.
2) Comprehends widely used random variables (such as Uniform, Gaussian, Poisson, etc.).
3) Compute the moments of random variables including the mean and variance.
4) Characterize multiple random variables using joint distribution functions.
5) Understand the law of large numbers and the central limit theorem.
6) Use statistical concepts and tools to interpret engineering data.

Course Flow Plan

Week	Subject	Related Preparation
1)	Sample spaces and probability
2)	Bayes rule and independence
3)	Counting and combinatorics
4)	Discrete random variables
5)	Discrete random variables
6)	Discrete random variables
7)	Continuous random variables
8)	Midterm Exam
9)	Continuous random variables
10)	Continuous random variables
11)	Sampling distributions
12)	Confidence intervals
13)	Hypothesis testing
14)	Linear regression

Sources

Course Notes / Textbooks:	Walpole, M. (2016). Probability and Statistics for Engineers and Scientists (9th/Global edition), Pearson Education.
References:	Baron, M. (2014/2019). Probability and Statistics for Computer Scientists (2nd or 3rd edition), CRC Press / Taylor & Francis. Richard A. Johnson. Probability and Statistics for Engineers (Ninth/Global Edition), Pearson.

Course - Program Learning Outcome Relationship

Course Learning Outcomes	1	2	3	4	5	6
Program Outcomes
1) Adequate knowledge in mathematics, science, and computer engineering principles, both theoretical and practical, and the ability to apply this knowledge to complex engineering problems.	3	3	3	3	3	3
2) Ability to identify, formulate, and solve complex computer engineering problems using appropriate analysis and modeling techniques.
3) Ability to design and develop complex computer systems, devices, or products that meet specific requirements and operate under realistic constraints and conditions, using modern design methods.
4) Ability to develop, select and use modern techniques and tools used for the analysis and solution of complex computer engineering problems, and the ability to use information technologies effectively.
5) Ability to plan and conduct experiments, collect and analyze data, and interpret results in the study of complex computer engineering problems or research topics.
6) Ability to work effectively within and multidisciplinary teams; individual study skills.
7) Ability to communicate effectively orally and in writing; knowledge of at least one foreign language; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8) Awareness of the necessity of lifelong learning; ability to access information, to follow developments in science and technology and to renew continuously.
9) To act in accordance with ethical principles, professional and ethical responsibility; information on the standards used in engineering applications.
10) Information on business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; information about sustainable development.
11) Knowledge of the effects of computer engineering practices on health, environment and safety in the universal and social scale and the problems of the era reflected in computer engineering; awareness of the legal consequences of computer engineering solutions.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Average	3 Highest

	Program Outcomes	Level of Contribution
1)	Adequate knowledge in mathematics, science, and computer engineering principles, both theoretical and practical, and the ability to apply this knowledge to complex engineering problems.	3
2)	Ability to identify, formulate, and solve complex computer engineering problems using appropriate analysis and modeling techniques.
3)	Ability to design and develop complex computer systems, devices, or products that meet specific requirements and operate under realistic constraints and conditions, using modern design methods.
4)	Ability to develop, select and use modern techniques and tools used for the analysis and solution of complex computer engineering problems, and the ability to use information technologies effectively.
5)	Ability to plan and conduct experiments, collect and analyze data, and interpret results in the study of complex computer engineering problems or research topics.
6)	Ability to work effectively within and multidisciplinary teams; individual study skills.
7)	Ability to communicate effectively orally and in writing; knowledge of at least one foreign language; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions.
8)	Awareness of the necessity of lifelong learning; ability to access information, to follow developments in science and technology and to renew continuously.
9)	To act in accordance with ethical principles, professional and ethical responsibility; information on the standards used in engineering applications.
10)	Information on business practices such as project management, risk management and change management; awareness of entrepreneurship and innovation; information about sustainable development.
11)	Knowledge of the effects of computer engineering practices on health, environment and safety in the universal and social scale and the problems of the era reflected in computer engineering; awareness of the legal consequences of computer engineering solutions.

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	1	% 40
Final	1	% 60
total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
total		% 100

Workload and ECTS Credit Calculation

Activities	Number of Activities	Preparation for the Activity	Spent for the Activity Itself	Completing the Activity Requirements	Workload
Course Hours	13	0	3		39
Application	13	0	2		26
Study Hours Out of Class	13	0	3		39
Midterms	1	13	2		15
Final	1	23	2		25
Total Workload					144