Probability and Random Variables
Software Engineering
Faculty of Engineering
First Cycle (Bachelor's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Probability and Random Variables | MUH202 | Compulsory | Bachelor's degree | 2 | Spring | 5 |
Name of Lecturer(s)
Assistant Prof. Dr. Mehmet Ali ALTUNCU
Prof. Dr. İrem BAĞLAN
Prof. Dr. Sevinç İLHAN OMURCA
Prof. Dr. Halil YİĞİT
Associate Prof. Dr. Orhan AKBULUT
Associate Prof. Dr. Sultan ALDIRMAZ ÇOLAK
Associate Prof. Dr. Suhap ŞAHİN
Associate Prof. Dr. Aysun TAŞYAPI ÇELEBİ
Assistant Prof. Dr. Metin BAYRAK
Assistant Prof. Dr. Arif DOLMA
Learning Outcomes of the Course Unit
1) Apply sample spaces and events for random experiments with graphs, tables, lists.
2) Calculate and Comment on interpret probabilities and use probabilities of outcomes to calculate probabilities of events in discrete/ continuous sample spaces and and calculate conditional probabilities of events.
3) Determine the independence of events and use independence to calculate probabilities
4) ) use Bayes’ theorem to calculate conditional probabilities.
5) ) Explain random variables.
6) determine probabilities from (discrete/continuous) probability mass functions.
7) Calculate means and variances for discrete/continuous random variables.
8) Use joint probability mass functions and joint probability density functions to calculate probabilities, and calculate marginal and conditional probability distributions from joint probability distributions.
Program Competencies-Learning Outcomes Relation
| Program Competencies | |||||||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | ||
| Learning Outcomes | |||||||||||||
| 1 | Middle | High | High | Middle | Middle | Low | Middle | Middle | Middle | Low | Middle | Low | |
| 2 | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Low | Low | Middle | Middle | |
| 3 | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Low | Low | Middle | |
| 4 | Middle | Middle | Middle | Middle | Low | Middle | Middle | Middle | Middle | Low | Middle | High | |
| 5 | Middle | Middle | Middle | Low | Middle | Middle | High | Middle | Middle | Middle | Middle | High | |
| 6 | Middle | Middle | Middle | Middle | Middle | High | Middle | Middle | Middle | Low | High | High | |
| 7 | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Low | High | High | |
| 8 | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | Middle | High | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
image Processing
Course Contents
This course covers ;introduction, statistics, some concepts used in statistics, processing of the data, statistical probability, measures of variability, probability theory, conditional probability, Bayes Theorem,probability distributions,probability distribution function,characteristics of probability distributions,measures, some special probability distributions,special discrete distributions,special permanent,distributions,two-dimensional probability distribution,some two-dimensional distributions, two random elimination of one variable, probability density function of a random variable, characteristic function of a random variable and application of a communication channel.
Weekly Schedule
1) Introduction to Probability2) Statistics. Some concepts used in statistics
3) Processing of the data. Statistical Probability.
4) Measures of variability.
5) Probability Theory. Conditional Probability. Bayes Theorem.
6) Probability distributions. Probability distribution function.
7) Characteristics of Probability Distributions Measures.
8) Midterm examination/Assessment
9) Special Discrete Distributions. Special continuous Distributions.
10) Two-dimensional probability distribution.
11) Some Two-Dimensional Distributions.
12) Two random Elimination of one variable.
13) Probability Density Function of a Random Variable.
14) Characteristic Function of a Random Variable.
15) Some Special Probability Distributions. Application of a communication channel,
16) Final examination
Recommended or Required Reading
1- Ders Notları
2- A First Course in Probability, S. Ross, Sixth Ed., Prentice-Hall, 2002.
3- Introduction to Probability and Statistics, J.S., Milton,
J.C., Arnold, MacGraw Hill,USA.,1995.
4- Introduction to Mathematical Statistics, R.V.Hogg and A.T. Craig,
Collier MacMillan, USA.,1995.
5- Ders Notları
6- A First Course in Probability, S. Ross, Sixth Ed., Prentice-Hall, 2002.
Planned Learning Activities and Teaching Methods
1) Lecture
2) Simulation
3) Case Study
4) Problem Solving
5) Project Based Learning
Assessment Methods and Criteria
Contribution of Midterm Examination to Course Grade |
30% |
|---|---|
Contribution of Final Examination to Course Grade |
70% |
Total |
100% |
Language of Instruction
Turkish
Work Placement(s)
Not Required