Course Title Course Code Program Level

Course Term
(Course Semester)
Teaching and Learning Methods
Theory Practice Lab Projects/Field Work Seminars/Workshops Other Total Credits ECTS Credits
28 14 28 70 140 3 5

Teaching Staff
Language of Instruction Türkçe (Turkish)
Type Of Course Compulsory
Prerequisites None
Recommended Optional Programme Component
Course Objectives Course aims to introduce descriptive statistics and probability theory.
Course Content Descriptive statistics, probability theory, various distributions, sampling distribution, hypothesis.
Learning Outcomes (LO) Upon successful completion of the course, students will be able to use and apply descriptive statistics and probability theory.
Mode of Delivery Face to face
Course Outline
Week Topics
1. Week Introduction, basic concepts, measurement levels of variables
2. Week Statistical data and frequency distributions
3. Week Figures/Graphs
4. Week Measures of central tendency
5. Week Measures of distribution
6. Week Basic concepts of probability
7. Week Expected Value and Variance of Random Variables
8. Week Bernoulli and binomial distributions
9. Week Poisson distribution
10. Week Normal distribution
11. Week Application of normal distribution
12. Week Sampling distribution, central limit theorem
13. Week Hypothesis concepts and types of error
14. Week Hypothesis testes related to mean
Mid-term (%) 40
Quizes (%)
Homeworks/Term papers (%)
Practice (%)
Labs (%)
Projects/Field Work (%)
Seminars/Workshops (%)
Final (%) 60
Other (%)
Total(%) 100
Course Book (s) and/or References Ünver, Ö., Gamgam H., 2008, Uygulamalı Temel İstatistik Yöntemler, Seçkin, Ankara. Bluman, Allan, G., 2004, Elementary Statistics, Mc Graw Hill
Work Placement(s)
The Relationship between Program Qualifications (PQ) and Course Learning Outcomes (LO)