Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
PROBABILITY UAKT101 1. Semester 2 + 2 3.0 5.0

Prerequisites None

Language of Instruction Turkish
Course Level Bachelor's Degree
Course Type Compulsory
Mode of delivery Computer aided oral presentation
Course Coordinator
Instructors
Assistants
Goals Aims of this course are to get the students through the randomness along with probability, concept of continuous and discrete probability distribution, marginal and joint probability distributions in order to make probabilistic modelling.
Course Content Some tools and discrete probability distributions for modeling problems which inherit randomness.
Learning Outcomes 1) Describe concept of theoretical probability
2) Infer conditional probability
3) Understand ındependency
4) Use Bayes theorem
5) Use discrete probability functions
6) Use continuous probability density functions
7) Use distribution functions
8) Make transformation

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
1. Week Sets, operations with sets, set classes, sigma algebra, introducing Borel algebra with some of its elements Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
2. Week Experiments with random results, sample point, sample spaces and events. Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
3. Week Probability measures, probability spaces and some examples. Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
4. Week Conditional probability, total probability rule, Bayes rule and independence of events. Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
5. Week Modeling experiments with random results, finite sample spaces, counting techniques, and some probability problems. Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
6. Week Discrete and continuous sample spaces, probability models related to these sample spaces and geometric probability Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
7. Week Random variables and distribution functions Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
8. Week Midterm exam Question Answer; Problem Solving
9. Week Discrete random variables and probability mass functions Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
10. Week Expected values, variances and moment generating functions of discrete random variables Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
11. Week Uniform, Bernoulli, binomial distributions and their places of usage as model Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
12. Week Geometric, negative binomial distributions and their places of usage as model Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
13. Week Hyper geometric distribution and its comparison with binomial distribution, multinomial distribution Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
14. Week Poisson distribution and its places of usage as model Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
15. Week Preparation for final exam Lecture; Question Answer; Problem Solving; Discussion

 Homework Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
16. Week Final exam Question Answer; Problem Solving

Sources Used in This Course
Recommended Sources
Lee, P. M., 1989, Bayesian Statistics: An Introduction University of York, England.
Press, S.J.,1989 “Bayesian Statistics: Principles, Models and Applications”, John Wiley and Sons, New York, 1989.
Wackerly D.D., Mendenhall W.,Scheaffer R.L., 2008, Mathematical Statistics with Applications, Thomson.

Relations with Education Attainment Program Course Competencies
Program RequirementsContribution LevelDK1DK2DK3DK4DK5DK6DK7DK8
PY1500000000
PY2500000000
PY3500000000
PY4500000000
PY5500000000

*DK = Course's Contrubution.
0 1 2 3 4 5
Level of contribution None Very Low Low Fair High Very High
.

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 15 5
Work Hour outside Classroom (Preparation, strengthening) 15 5
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
Quick Access Hızlı Erişim Genişlet
Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • Relations with Education Attainment Program Course Competencies
  • ECTS credits and course workload