Course Information

Course Information
Course Title Code Semester L+U Hour Credits ECTS
Probability and Statistics EEM267 3. Semester 3 + 0 3.0 5.0
Prerequisites None
Language of Instruction Turkish
Course Level Undergraduate
Course Type
Mode of delivery Face-to-face and online
Course Coordinator Assoc. Prof. Dr. Selman KULAÇ
Assist. Prof. Dr. OSMAN DİKMEN
Res. Assist. Elif Eda TAKGİL
Instructors OSMAN DİKMEN
Assistants
Goals To enable students to learn probabilistic and statistical concepts that they can use in electrical-electronic system analysis and design, especially communication systems. In addition, relevant current issues are researched and presented in the classroom environment.
Course Content 1. Introduction to probability 2. Discrete and continuous random variables 3. Two-dimensional distributions 4. Short introduction 5. Statistical hypothesis testing and linear models 6. Regression and Analysis of Variance
Learning Outcomes - To learn basic probability concepts
- To have knowledge about random variables and probability functions
- To have knowledge about discrete and continous distributions
- To learn basic statistical concepts
- To have knowledge about statistical analysis methods
Weekly Topics (Content)
Week Topics Learning Methods
1. Week Introduction to probability, sample space and event, joint event, probability axioms
2. Week Conditional probability, tree diagrams, total probability formula, Bayes' theorem, independence
3. Week Distribution and density functions of continuous and discrete random variables, mean and standard deviation values
4. Week Moment concept, relationship between moments, Chebyshev inequality
5. Week Bivariate (joint) discrete and continuous random variables
6. Week Conditional probability distributions, sample problems
7. Week Concepts of covariance, correlation and correlation coefficient
8. Week Solving questions
9. Week Discrete distributions: bernoulli, binomial, negative binomial, geometric, poisson and hypergeometric
10. Week Continuous distributions: uıniform, exponential, normal distributions
11. Week Sampling, statistical estimation, confidence intervals
12. Week Hypothesis testing, power of test, independence test
13. Week Regression analysis: linear regression, least squares method, multiple regression
14. Week Variance analysis
Recommended Sources
1. Prof. Dr. Fikri Akdeniz, Olasılık ve İstatistik, 2016, Akademisyen Kitabevi
2. Prof. Dr. Aydın ÜSTÜN, Olasılık ve İstatistik, 2014 (Taslak)
3. Stark, H., Woods J. W., Probabiliy and Random Processes with Applications to Signal Processing, Third edition, Prentice Hall, 2002
4. Papoulis A., Pillai S.U., Probability, Random Variables and Stochastic Processes, Fourth edition, McGraw Hill, 2002.
Relations with Education Attainment Program Course Competencies
Program Requirements Contribution Level DK1 DK2 DK3 DK4 DK5 Measurement Method
PY1 4 4 4 4 4 4 40,60
PY2 4 4 4 4 4 4 40,60
PY3 3 3 3 3 3 3 40,60
PY4 3 3 3 3 3 3 40,60
PY5 3 3 3 3 3 3 40,60
PY6 2 2 2 2 2 2 40,60
PY7 2 2 2 2 2 2 40,60
PY8 2 2 2 2 2 2 40,60
PY9 0 0 0 0 0 0 40,60
PY10 0 0 0 0 0 0 40,60
PY11 0 0 0 0 0 0 40,60
*DK = Course's Contrubution.
0 1 2 3 4 5
Course's Level of contribution None Very Low Low Fair High Very High
Method of assessment/evaluation Written exam Oral Exams Assignment/Project Laboratory work Presentation/Seminar
ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Midterm 1 1 25 25
Homework 1 1 15 15
Final 1 25 25
Practice 1 10 10
Practice End-Of-Term 1 10.5 10.5
Classroom Activities 14 3 42
Total Workload 127.5
ECTS Credit of the Course 5.0