Information Package / Course Catalogue
Probability and Statistics I
Course Code: MAT211
Course Type: Required
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 2
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

To introduce the fundamental concepts of probability theory, develop students' ability to model random phenomena mathematically, and enable them to apply basic probability distributions to real-world problems.

Course Content

Counting techniques, sample spaces and events, probability axioms, conditional probability, independence, Bayes' theorem, random variables, distribution functions, expectation, variance, moments, Bernoulli, Binomial, Geometric, Hypergeometric, Poisson, Uniform, Exponential and Normal distributions.

Name of Lecturer(s)
Learning Outcomes
1.Apply counting techniques and fundamental probability rules.
2.Solve problems involving conditional probability and Bayes' theorem.
3.Explain the concepts of random variables and probability distribution functions.
4.Calculate expectation, variance and standard deviation.
5.Apply discrete and continuous probability distributions.
6.Construct probabilistic models for real-world problems and interpret the results.
Recommended or Required Reading
1.Olasılık ve İstatistik, Fikri Akdeniz, Akademisyen Kitabevi, Ankara, 2022.
2.Modern Probability and Its Applications, Mood A.M., Graybill F.A. McGraw-Hill Book Company, New York, 1963.
3.Introduction to Probability and Statistics, Mendenhall, W., Beaver, R. J., & Beaver, B. M.,15th Ed., Cengage Learning, 2019.
Weekly Detailed Course Contents
Week 1 - Theoretical & Practice
Counting Techniques
Week 2 - Theoretical & Practice
Permutations and Combinations
Week 3 - Theoretical & Practice
Basic Concepts of Probability
Week 4 - Theoretical & Practice
Probability Axioms and Theorems
Week 5 - Theoretical & Practice
Conditional Probability
Week 6 - Theoretical & Practice
Independent Events and Bayes' Theorem
Week 7 - Theoretical & Practice
Random Variables
Week 8 - Theoretical & Practice
Distribution Functions
Week 9 - Theoretical & Practice
Expectation and Variance
Week 10 - Theoretical & Practice
Bernoulli and Binomial Distributions
Week 11 - Theoretical & Practice
Geometric and Hypergeometric Distributions
Week 12 - Theoretical & Practice
Poisson Distribution
Week 13 - Theoretical & Practice
Uniform and Exponential Distributions
Week 14 - Theoretical & Practice
Normal Distribution and Applications
Assessment Methods and Criteria
Type of AssessmentCountPercent
Assignment1%5
Term Assignment1%5
Midterm Examination1%30
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Lecture - Practice140228
Assignment1213
Term Project1224
Individual Work140114
Midterm Examination118220
Final Examination126228
TOTAL WORKLOAD (hours)125
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
PÇ-13
PÇ-14
PÇ-15
PÇ-16
PÇ-17
PÇ-18
OÇ-1
3
4
1
3
3
4
4
4
4
3
4
3
OÇ-2
3
4
2
3
3
4
4
4
4
3
4
2
OÇ-3
2
3
3
3
3
2
4
4
4
3
4
2
OÇ-4
2
2
4
3
3
2
4
4
4
3
4
1
OÇ-5
3
3
4
3
3
4
4
4
4
3
4
3
OÇ-6
4
2
3
2
3
4
3
4
3
2
3
3
Adnan Menderes University - Information Package / Course Catalogue
2026