COMPUTER ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
MAT3026	Probability and Statistics	Spring	3	0	3	6

Basic information

Language of instruction:	English
Type of course:	Must Course
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Instructor NERMINE AHMED EL SISSI
Course Lecturer(s):	Dr. Öğr. Üyesi MÜRÜVVET ASLI AYDIN
Recommended Optional Program Components:	None
Course Objectives:	Topics in probability and statistics are introduced through their definitions leading to the development of basic probabilistic and statistical tools. Emphasis is placed on using these tools to solve engineering problems and to make informed decisions.

Learning Outcomes

The students who have succeeded in this course;
1) Calculate probability using permutations and combinations
2) Calculate probability of unions and intersects
3) Determine the reliability block diagram of a system of elements
4) Understand the conditional probability an apply on probability problems
5) Calculate probability using probability distribution functions
6) Calculate expectation values
7) Apply hypothesis testing
8) Determine confidence intervals

Course Content

The course will cover the following topics:
Counting and probability (both theoretical and experimental definitions);
Rules of probability (based on set theory); conditional probability;
The random variable; probability mass functions and density functions;
Expectation values; sampling theory (mean and standard deviation); hypothesis testing;
Confidence intervals (for the population mean, population standard deviation).

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to the course.
2)	Counting and probability.
3)	Rules of Probability (sets, additive rules, independence), the Reliability Block Diagram.
4)	Conditional probability (independence, Bayes' theory).
5)	The random variable, and probability distributions (discrete and continuous) \ review.
6)	Expectation values: the population mean.
7)	Expectation values: the population standard deviation.
8)	Special discrete distributions (Geometric, Hypergeometric, Binomial, Poisson).
9)	Special continuous distributions (Exponential, Weibull, Normal).
10)	Sampling (the sampled mean and standard deviation, and their distributions) \ review.
11)	Hypothesis testing (p-values for the mean and standard deviation, t- and chi-square-distributions).
12)	Confidence intervals I - intervals for the mean, pairing, standard error in the sample mean.
13)	Confidence intervals II - intervals for the mean (two population)
14)	Confidence intervals III - intervals for the standard deviation.

Sources

Course Notes / Textbooks:	Walpole, Ronald E., et al. "Probability & Statistics for Engineers & Scientists", Prentice Hall, 9th ed.
References:	Douglas C. Montgomery & George C. Runger. "Applied Statistics and Probability for Engineers”; (2011) Wiley. Devore, Jay.; "Probability & Statistics for Engineering and the Sciences". CengageBrain.com.

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Midterms	2	% 60
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	7	98
Midterms	1	2	2
Final	1	2	2
Total Workload			144

Contribution of Learning Outcomes to Programme Outcomes

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

	Program Outcomes	Level of Contribution
1)	Adequate knowledge in mathematics, science and computer engineering; the ability to use theoretical and practical knowledge in these areas in complex engineering problems.	5
2)	Ability to identify, formulate, and solve complex engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose.	5
3)	Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose.
4)	Ability to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in computer engineering applications; ability to use information technologies effectively.
5)	Ability to design, conduct experiments, collect data, analyze and interpret results for the study of complex engineering problems or computer engineering research topics.	3
6)	Ability to work effectively within and multi-disciplinary teams; individual study skills.
7)	Ability to communicate effectively in verbal and written Turkish; knowledge of at least one foreign language; ability to write active 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 engineering practices on health, environment and safety in the universal and social scale and the problems of the era reflected in engineering; awareness of the legal consequences of engineering solutions.