Course Name Code Semester T+U Hours Credit ECTS
Probability and Statistics IST 204 4 3 + 0 3 5
Precondition Courses MAT 111 , MAT 112
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Compulsory
Course Coordinator Dr.Öğr.Üyesi TÜRKER FEDAİ ÇAVUŞ
Course Lecturers Dr.Öğr.Üyesi GÖKÇEN ÇETİNEL, Dr.Öğr.Üyesi TÜRKER FEDAİ ÇAVUŞ,
Course Assistants
Course Category Available Basic Education in the Field
Course Objective Introduce statistical concepts and techniques required analysis of electrical and electronics systems especially communication systems
Course Content Introduction to probability, discrete random variables, continuous random variables, distributions involving two random variables, introduction to statistical parameter estimation, statistical hypothesis testing, linear models
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Understanding the concept of a random variable Lecture, Question-Answer, Discussion, Problem Solving, Testing, Homework,
2 Obtaining a working knowledge on probability density function Lecture, Question-Answer, Problem Solving, Testing, Oral Exam, Homework,
3 Learning the concept of expected value of a random variable Lecture, Question-Answer, Problem Solving, Testing, Oral Exam, Homework,
4 Discussing statistical parameter estimation Lecture, Question-Answer, Discussion, Problem Solving, Testing, Oral Exam, Homework,
5 Learning statistical hypothesis testing Lecture, Question-Answer, Problem Solving, Testing, Oral Exam, Homework,
Week Course Topics Preliminary Preparation
1 Introduction to probability, sample space and event, composite event, probability axioms, finite probability spaces
2 Conditional probability, conditional probability axioms, Bayes Theorem, independence, repeated trials
3 Probability distribution function, probability density function, expected value and variance of discrete and continuous random variables
4 Concept of moment, relationship between moments, moment generating function, Chebyshev inequality, the law of large numbers
5 Discrete distributions: Bernoulli, binomial, multinomial, geometric, Poisson and hypergeometric distributions
6 Continuous distributions: Uniform, exponential and Normal distributions
7 Gamma, chi-square, student-t and beta distributions
8 Discrete and continuous distributions with two random variables
9 Conditional probability density function
10 Concepts of covariance, correlation and correlation coefficient
11 Sampling, statistical parameter estimation, confidence intervals for parameter estimation
12 Hypothesis tests, power of the test, independence test
13 Regression analysis: linear regression, the least squares method, multivariate regression
14 Variance analysis
Course Notes
Course Resources
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in complex engineering problems. X
2 Ability to identify formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
3 Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues, according to the nature of the design.)
4 Ability to devise, select, and use modem techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
5 Ability to design and conduct experiments, gather data analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
6 Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7 Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
8 Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
9 Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice.
10 Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.
11 Knowledge about the global and social effects of engineering practice on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.
Evaluation System
Semester Studies Contribution Rate
1. Kısa Sınav 15
2. Kısa Sınav 15
1. Ara Sınav 55
3. Kısa Sınav 15
Total 100
1. Yıl İçinin Başarıya 40
1. Final 60
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 10 10
Assignment 1 5 5
Final examination 1 15 15
Total Workload 126
Total Workload / 25 (Hours) 5.04
dersAKTSKredisi 5