          Description of Individual Course Units
 Course Unit Code Course Unit Title Type of Course Unit Year of Study Semester Number of ECTS Credits İST201 PROBABILITY Compulsory 2 3 7
Level of Course Unit
First Cycle
Objectives of the Course
The aim of this course is to comprehend the asimptotic structure of the theory of statistics forming a basis to subject of statistics and in solving problems obtaining the ability of applying this structure.
Name of Lecturer(s)
Prof. Dr. Onur KÖKSOY
Learning Outcomes
 1 To be able to express the concepts of the theory of statistics depending on the concepts of sets. 2 To be able to prove the teorems of probability depending on the set concepts. 3 To be able to use the gained knowledge in solving the problems. 4 To be able to analyse the discrete and continuous random variables and their probability distributions. 5 To be able to distinguish distribution function and cumulative distribution function.
Mode of Delivery
Face to Face
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Course Contents
Concept of Probability, Sample space and events, Some relations from set theory, Axioms, properties of probability, Principles of counting: Basic Prensiple of counting, Conditional probability, The multiplication rule, Independence, Discrete random variables and Probability distributions, Cumulative distribution function, random variable and the expected value of a function of a random variable, Bernoulli,Binomial, Hypergeometric and Negative Binomial Distributions and properties, Generalization of Binomial distribution for Poisson Distribution, Continuous Random variables and Probability Distributions, Cumulative Distribution functions and expected values, Normal Distribution, Gamma Distribution and derivates, Other continuous distributions, Joint Probability distributions and density functions, Marginal Probability distribution functions and density functions, Joint Probability Distibution functions, Expected value, Covariance, Correlation
Weekly Detailed Course Contents
 Week Theoretical Practice Laboratory 1 Definitions on Probability theory 2 Set theory and relations 3 Properties of probability concept and axioms 4 Counting techniques, permutation, combination 5 Conditional probbaility, multiplication rule and concepts of independence 6 Discrete random variables, probability distributions, Cumulative distribution function and expected value 7 Special disributions and basic properties 8 Mid-term Examination 9 Continuous random variables and probability distributions 10 Cumulative distribution function and expected value 11 Continuous distributions and basic properties 12 Joint probability distribution and probability density function 13 Marginal probability distribution function and density function 14 Joint cumulative distribution functions 15 Expected value, covariance and correlation 16 Final Examination
Hogg, R., V., Tannis, E., A., “Probability and Statistical Inference”, Mendenhall, W., “Introduction to Probability and Statistşcs”, University of Florida, Emerritus (1997), Jay L. Devore, “Probability and Statistics for Engineering and the Sciences” (1997)
Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
 Term (or Year) Learning Activities Quantity Weight Midterm Examination 1 100 SUM 100 End Of Term (or Year) Learning Activities Quantity Weight Final Sınavı 1 100 SUM 100 Term (or Year) Learning Activities 40 End Of Term (or Year) Learning Activities 60 SUM 100
Language of Instruction
English
Work Placement(s)
None 